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Universal Investment Model

Part 2.A Mission

Investment tools that work for any industry — Valuation / Mental Models / Historical Analogs / Portfolio / Behavioral Finance. After completing Part 2.A, your toolkit is complete — not just for AI, you can dissect any stock.

Part 2.A Backbone

5 independent tools, not interdependent, but strongest when used together. Valuation (C1) gives numbers, Mental Models (C2) give perspective, History (C3) gives base rates, Sizing (C4) gives action, Behavior (C5) gives discipline.


5-Chapter Map

# Title Core One-Liner Est. Time
C1 Valuation Basics (DCF / Multiples / Margin of Safety) Price is what you pay, value is what you get 1 hr
C2 Mental Models (Buffett / Munger / Graham) Latticework, 70+ interdisciplinary frameworks interwoven 1 hr
C3 Historical Analogs (Dotcom / Mobile / Industrial Revolution) Find AI's historical anchor 1 hr
C4 Portfolio Construction Sizing matters more than picking 1 hr
C5 Behavioral Finance (6 Biases) Your biggest opponent isn't the market, it's you 1 hr

Part 2.A vs. Part 2.B Relationship

Part 2.A Gives You Part 2.B Uses It
Valuation fair value range (C1) P2B-C2 thesis yaml adds price_outlook
Mental Models (C2) P2B-C2 4-dimension thesis sanity-checked by 5 models
Historical base rate (C3) P2B-C5 90-day review compares to base rate
Sizing (C4) P2B-C5 determines position size
6 bias hacks (C5) Applied throughout the entire investment process

  • Day 1: C1 Valuation (basic numerical tool)
  • Day 2: C2 Mental Models (thinking frameworks)
  • Day 3: C3 Historical Analogs (base rate)
  • Day 4: C4 Portfolio (sizing decisions)
  • Day 5: C5 Behavioral Finance (self-hacking)

Part 2.A Completion Self-Check

  • Calculate fair value range + margin of safety for 1 stock
  • Evaluate 1 thesis using 5 Mental Models
  • Find which historical paradigm AI most resembles
  • Reasonably size a 5-10 stock portfolio
  • Identify your 2-3 most common behavioral biases

All 5 ✓ → Proceed to AI-Specific Analysis. Any ✗ → Return to the corresponding chapter to review.


Part 2.A Is Foundational, Not Advanced

Everything taught in Part 2.A is classic frameworks from 1934-2010 (Graham / Buffett / Munger / Kahneman). Not trendy, but always works. AI-era specialized tools are in Part 2.B, but they build on Part 2.A.