bottleneck-hunter

# Supply-Chain Bottleneck Hunter Decompose a super-trend (user-specified, e.g. "AI infrastructure", "energy transition") into its physical supply chain and hunt for bottleneck-arbitrage opportunities. ## Core Idea Don't ask "which AI stock to buy" — ask "if this trend keeps expanding, which link runs out first?" Traditional research chases leaders and known tracks. This skill inverts: **start from the choke points of the physical supply chain and find companies nobody notices but that the whole industry must wait on when they run short.** The edge: Layer-1 bottlenecks (GPU, HBM, power) are already priced in. The real alpha is in **Layer 2 and Layer 3** — optical modules, lasers, InP substrates, SOI wafers, epitaxy equipment, wafer-level test, IC substrates, specialty fiberglass. ## Step 1: Super-Trend Confirmation ### Trend Filter Criteria | Criterion | Requirement | How to verify | |-----------|-------------|---------------| | Durability | ≥3-5 years of certain growth | Search industry forecasts, capex plans | | Physicality | Needs real hardware/material/equipment build | Distinguish "software upgrade" from "physical expansion" | | Scale | Global capex >$50B/year | Search top players' capex guidance | | Acceleration | Demand growth > supply expansion | Compare demand growth vs capacity plans | Use `web_search` to verify. Reference super-trends: AI infrastructure, energy transition (nuclear/grid/storage), defense modernization, semiconductor reshoring, space economy. ## Step 2: Physical Supply-Chain Decomposition Don't stop at concepts — decompose to physical entities. ``` Layer 0 (end): final product/service Layer 1 (core component): already closely watched → priced in, limited alpha Layer 2 (sub-component/material): low attention, alpha-rich Layer 3 (upstream equipment/raw material) Layer 4 (infrastructure): power, cooling, land, talent, certifications ``` ### AI Infrastructure Example ``` Layer 0: AI model training/inference services Layer 1: GPU/accelerators, HBM, servers, data centers Layer 2 (focus zone): - Network interconnect: optical modules, fiber, switch ASICs, copper cables - Optical comms core: lasers (EML/VCSEL/CW), modulators, photodetectors - Semiconductor materials: InP substrates, GaAs substrates, SOI wafers, SiC substrates - Advanced packaging: CoWoS interposers, HBM TSV, ABF substrate film - PCB/substrate: high-frequency PCB, IC substrates, specialty fiberglass - Test: wafer-level test (probe cards), burn-in, ATE - Thermal/cooling: liquid cooling, CDU, immersion fluid - Power connection: busbars, UPS, distribution, transformers Layer 3: epitaxy equipment (MOCVD/MBE), lithography/etch, high-purity metals (In/Ga/Ge), specialty gases, sputtering targets, certifications (MSA/Telcordia) Layer 4: power (nuclear/gas/transmission), cooling water, data-center land/permits ``` For other trends, use `web_search` with queries like `{trend} supply chain bottleneck`, `{trend} shortage critical component`, `{trend} capacity constraint`, `{trend} sole source supplier`. ## Step 3: Bottleneck Identification — Finding "Choke Points" For each Layer 2-3 link, evaluate 6 criteria: | # | Criterion | Question | Score | |---|-----------|----------|-------| | 1 | Supply concentration | ≤3 global suppliers? | 🔴 ≤2 / 🟡 3-5 / 🟢 >5 | | 2 | Expansion lead time | How long to add capacity? | 🔴 >2y / 🟡 1-2y / 🟢 <1y | | 3 | Substitutability | Can other tech/material replace it? | 🔴 irreplaceable / 🟡 partial / 🟢 easy | | 4 | Capacity utilization | Current utilization? | 🔴 >90% / 🟡 70-90% / 🟢 <70% | | 5 | Demand growth | Downstream demand growth? | 🔴 >50%/yr / 🟡 20-50% / 🟢 <20% | | 6 | Customer qualification cycle | How long for a new supplier to qualify? | 🔴 >1y / 🟡 6-12m / 🟢 <6m | **Bottleneck grade**: 🔴×≥4 → **S-grade** (single-point failure, highest priority); 🔴×3 → **A-grade** (severely constrained); 🔴×1-2 → **B-grade** (stressed but manageable); no 🔴 → not a bottleneck, skip. ## Step 4: Company Screening — From Bottleneck to Tickers For each S/A-grade bottleneck, use `web_search` / `screen_market` to find listed companies. ### Initial Screen | Criterion | Requirement | |-----------|-------------| | Listing status | Listed (A/HK/US/JP/TW/EU) | | Bottleneck revenue share | >30% of revenue from the bottleneck link | | Market cap | Prefer <$10B (large caps already priced) | | Liquidity | Average daily turnover >$1M | ### Valuation Gate (mandatory, never skip) **A real bottleneck ≠ an investment opportunity.** For every company, compute PE/PB/ROE/FCF yield with `financial_rigor` (`command=verify_valuation`), and run `financial_rigor` (`command=three_scenario`) for scenario valuation: - **Red light** (any one → signal strength capped at ★★, flag "valuation stretched"): market cap >20% of TAM; PS>30x with revenue growth <100%; market cap >10× 5-year optimistic revenue forecast; stock doubled within 60 days of a follow-on offering. - **Yellow light** (needs extra justification, else downgrade): loss-making + PS>15x; PS >5× a profitable peer; PE>80x (compute PEG). - **Green light** (bonus): PS<10x with revenue growing; PE<30x with a moat (flag "margin of safety"). **Sanity check (mandatory)**: with `financial_rigor` (`command=three_scenario`), answer — "buying at current market cap, if the most optimistic scenario fully plays out and I exit at 25× PE in 10 years, what's the annualized return?" <10%/yr → flag "no margin of safety at current price". ## Step 5: Cross-Validation — Don't Trust a Single Story ### Positive checks | Check | Question | |-------|----------| | Customer validation | Have top customers signed/imported? (check announcements, customer filings) | | Revenue validation | Is the bottleneck already showing in revenue growth? (last 2-3 quarters) | | Price validation | Is the product raising price? (industry quotes, analyst reports) | | Capacity validation | Is capacity really tight? (lead times, customer complaints) | | Capital validation | Is there expansion capex? (company guidance) | Use `get_financial_statements` / `get_stock_news` / `web_search`. ### Reverse checks (Munger inversion) - Why don't smart people buy this stock? - Can the bottleneck be bypassed? Alternative routes? - Can China / other players quickly replicate capacity? - If end-demand drops 50%, what happens to this company? - Has management diluted at highs before? - What growth assumption does the current valuation imply? ## Step 6: Output — Bottleneck Opportunity Board ### Ranking Table | Rank | Company | Ticker | Mkt Cap | Revenue | PS | PE | Bottleneck link | Grade | Share | Growth | Signal | Valuation | |------|---------|--------|---------|---------|-----|-----|-----------------|-------|-------|--------|--------|-----------| **Market cap, revenue, PS, PE are mandatory** — never skip with "TBD". If financials can't be obtained, signal strength ≤★★. Signal strength (valuation gate directly affects): - ★★★★★ multi-cross-validated + customers imported + revenue confirmed + valuation green - ★★★★ most checks pass + valuation green/yellow (with explanation) - ★★★ logic holds but parts unverified + valuation yellow acceptable - ★★ early signal, or logic holds but valuation red - ★ pure concept, unverified After drafting, run `report_audit` (`command=extract` → verify each point → `command=verdict`) as a quality gate to ensure no hallucinated numbers. ### One-Pager Template ``` 🎯 {Company} ({Ticker}) — {one-line bottleneck positioning} Why it's a bottleneck: (2-3 sentences) Why this company: (2-3 sentences) Catalyst timeline: - Near-term (1-3m): [earnings / capacity / customer win] - Mid-term (3-12m): [industry trend / expansion node] Key risks: 1. 2. Key data: market cap / revenue / PS / PE / growth / bottleneck revenue share Margin of safety: 10y 25× PE exit method, annualized return XX%. Conclusion: yes/no. Cross-validation status: ✅ customer / ✅ revenue / ⚠️ valuation stretched / ❌ unverified Conclusion: deep research / watchlist / skip ``` Save with `write_file` to the reports directory (e.g. `reports/bottleneck-map/{trend}-bottleneck-{YYYYMMDD}.md`). ## Step 7: Inventory Update — Maintain the Bottleneck Map On each run: ① re-check identified bottlenecks (new suppliers? capacity expanded? substitute breakthrough?); ② scan new bottlenecks (`web_search` last 7 days supply chain / shortage / bottleneck news); ③ update grades (upgrade/downgrade/relieve). ## AI Research Bias Self-Check | Bias | Symptom | Counter | |------|---------|---------| | Leader-bias | Search dominated by large caps | Deliberately search small-cap suppliers, add "small cap" | | English-bias | Miss JP/KR/TW players | Must search JP/KR/TW market suppliers | | Narrative-bias | Drawn to "AI concept" labels | Look only at actual supply-chain position, not market labels | | Confirmation-bias | After finding a bottleneck, only seek positive evidence | Force Step 5 reverse checks | | Recency-bias | Rely on stale info | Prefer last 30 days of data | ## Core Principles (highest priority) 1. **Don't ask the AI to recommend stocks — ask it to decompose supply chains.** The question matters more than the answer. 2. **Physical first** — only links that need real physical product/material/equipment. 3. **Layer 2 and Layer 3** — don't chase already-priced leaders. 4. **Cross-validate** — every conclusion needs ≥2 independent sources. 5. **Be honest about uncertainty** — if data is missing, say so; don't fill with speculation. 6. **Bottlenecks are temporary** — every bottleneck gets resolved; the key is timing the window. 7. **Small cap ≠ good opportunity** — a small cap can also be a bad company; it must pass financial quality. 8. **A real bottleneck ≠ an investment** — at PS>30x or still loss-making, the current price is not a buy. **Valuation is a hard gate that cannot be overridden by bottleneck purity, signal strength, or narrative appeal.** Better to miss a bottleneck stock that ran than buy a loss-making company at 100× sales.