# Bayesian Evolution Assessment: Nanda & Lo Finance Lens ## πŸ… Prairie Food Literature Review | Paper | Core Concept | 🟒 AGREE | πŸ”΄ DISAGREE | πŸ’° Finance Application | | ------------------------------------------------------------------- | ---------------------------------------------------------------- | ------------------------------------------------ | ------------------------------------ | ---------------------------------------------------- | | **πŸ“œπŸ…_kerr14**<br>*systematize(experimentation, entrepreneurship)* | Entrepreneurship = experimentation with unknowable probabilities | **Strongly agree**: Captures venture uncertainty | - | Each funding round = experiment with capital at risk | | **πŸ“œπŸ…_granovetter78**<br>*model(collective-behavior, thresholds)* | Individual thresholds β†’ collective outcomes | Threshold models useful for herding | Too deterministic for markets | Explains funding cascades and crashes | | **πŸ“œπŸ‘Ύ_bolton24**<br>*moral_hazard* | Entrepreneurs design uninformative experiments | **Perfect fit**: Explains adverse selection | - | High Ο„ = manipulating investor signals | | **πŸ“œπŸ…_loch02**<br>*optimize(portfolio, selection)* | Marginal analysis for portfolio optimization | Portfolio thinking essential | Misses active uncertainty management | VCs optimize across (n,Ο„) space | | **πŸ“œπŸ…_kavadias03**<br>*sequence(projects, optimization)* | cΞΌ rule for project sequencing | Sequencing matters | Too rigid, assumes fixed parameters | Founders manipulate perceived urgency via Ο† | | **πŸ“œπŸ…_dada07**<br>*diversify(sourcing, suppliers)* | Diversification for risk management | Standard portfolio theory applies | Sometimes concentration optimal | High Ο„ justified when C > diversification benefit | | **πŸ“œhume**<br>*enquiry_human_understanding* | No necessary causation, instinct over reason | Philosophical foundation for uncertainty | - | Justifies why markets price "unknown unknowns" | --- ## πŸ’° Synthesis: From Capital Allocation to Uncertainty Design ### 🀠 채찍과거: The Information Asymmetry Obsession **What Finance Got Wrong:** - Venture capital as mere "funding gap" solution for collateral-less startups - Due diligence as torture chamber extracting every drop of information - Term sheets as straitjackets eliminating all degrees of freedom - Staged financing as progressive uncertainty elimination - IPO as ultimate victory of transparency over opacity - Better Place's perfect information set couldn't save $850M from burning ### πŸ₯• λ‹Ήκ·Όλ―Έλž˜: Uncertainty as Tradeable Asset **The Financial Revolution We Lead:** - **Ο„ as Asset Class**: Uncertainty has a price, and optimal portfolios diversify across (Ο„, n) space - **Staged Ο„ Evolution**: Seed(Ο„β‰ˆ2) β†’ Series A(Ο„β‰ˆ5) β†’ Growth(Ο„β‰ˆ8) as V/ic grows - **Productive Opacity**: High Ο„ commands premium when it signals irreversible commitment - **Exit Strategy Redesigned**: IPO forces Ο„β†’0 (commodity), M&A preserves Ο„>0 (strategic value) - **Tesla's Playbook**: Low initial Ο„ attracted capital, high final Ο„ created moat ### Key Financial Innovations from Our Model 1. **Valuation Formula**: Company value = f(Ο†, Ο„, n) not just f(expected cash flows) 2. **Optimal Staging**: Each round should trigger when V/ic crosses integer thresholds 3. **Portfolio Construction**: Diversify across (n,Ο„) space, not just industries 4. **Exit Timing**: IPO when Ο„ must β†’ 0; M&A while Ο„ > 0 still valuable 5. **Term Sheet Design**: Covenants should preserve optimal Ο„*, not minimize it --- ## Financial Mechanisms Mapped to Our Model | Our Parameter | Financial Interpretation | Market Mechanism | |---------------|-------------------------|------------------| | **Ο† (promise level)** | Implicit valuation claim | Term sheets, pitch decks | | **Ο„ (concentration)** | Information disclosure strategy | Due diligence resistance | | **n (complexity)** | Systematic/market risk | Beta, volatility measures | | **C (digestion cost)** | Due diligence expense | Legal, accounting, consultant fees | | **Learning trap** | Liquidation preference overhang | Down rounds, washouts | ## Capital Market Dynamics | Stage | Optimal Ο„ | Optimal n | Investor Type | Key Trade-off | | ------------ | --------- | --------- | -------------- | -------------------------------------- | | **Seed** | Low | High | Angels | Preserve optionality vs signal quality | | **Series A** | Rising | Medium | Early VCs | Build conviction vs maintain flexibility | | **Growth** | High | Low | Late VCs | Execute vision vs adapt to market | | **IPO** | Ο„β†’0 | Low | Public markets | Full transparency required | ## Risk-Return Implications | Portfolio Strategy | (n,Ο„) Coordinates | Expected Return | Risk Profile | |-------------------|-------------------|-----------------|--------------| | **Spray & Pray** | High n, Low Ο„ | Power law | Diversified | | **Conviction Bets** | Low n, High Ο„ | Binary | Concentrated | | **Index Approach** | Medium n, Ο„β†’0 | Market | Systematic only | | **Smart Money** | Variable n, Optimal Ο„* | Superior | Actively managed | ## Key Financial Insights 1. **Information Asymmetry as Feature**: Ο„ directly measures productive opacity 2. **Staging as Ο„ Evolution**: Each round optimally increases Ο„ as V/ic grows 3. **Valuation Premium**: High Ο„ commands premium when aligned with stage 4. **Exit Strategy**: IPO forces Ο„β†’0; strategic M&A preserves Ο„ value 5. **Market Cycles**: Bull markets reduce C β†’ higher optimal Ο„; Bear markets opposite --- *"Capital doesn't flow to the best ideas but to the best-designed uncertainties"* To flesh out this point, it is important to separate two frames of reference regarding experimentation. The first relates to economic experimentation in a Darwinian sense, which is the natural starting point for most economists. In this conceptual model, new ventures compete with existing products and technologies, and the ensuing competition leads to the survival of the fittest, just as Google surpassed its early rivals due to its superior technology.