Risk Science for Venture Capital
The first rigorous curriculum in risk management and portfolio analysis built specifically for venture capital GPs and LPs — derived from exploration science.
The Origin
For over a century, the natural resource industry has been making high-stakes decisions under radical uncertainty — drilling decisions worth hundreds of millions, in environments with no data, in markets no one fully understood.
They built rigorous frameworks for it: probabilistic risking, portfolio construction theory, calibration systems, and thematic capital allocation. The mathematics are precise. The discipline is deep.
No one has applied this body of knowledge to venture capital. Until now.
Full Curriculum
Each module maps directly to a decision that GPs and LPs face every day — now made with precision.
Identify and rank investment thematics before deal flow exists. The vertical you operate in determines your outcome distribution before you look at a single company. Build thematic EV models, estimate winner density, and allocate capital to environments — not companies.
The core survival model: Ps = Pv × Pc. Decompose startup risk into Venture Viability and Commercial Scaling. Score Team, Product, Traction, and Timing against Market, Distribution, Differentiation, and Competition. Once a company hits $1M ARR, Pv = 1.0.
Convert survival probability into chance-weighted exit value. Rank your entire pipeline by expected investment multiple. Set objective investment thresholds and build a dynamic deal funnel that improves continuously as new information arrives.
Model venture investments as sequential decisions under uncertainty. Use backward induction to evaluate follow-on strategy, reserve allocation, and the Value of Information before committing capital. Every investment is a sequence, not a single event.
Performance is driven by inventory, not individual picks. Build the largest possible unbiased deal universe, maintain 30%+ turnover, and construct portfolios that converge toward expected value rather than luck. Your future DPI is determined by the deals you're seeing today.
Risk is Uncertainty × Consequence. Price it, structure it, and manage it at the portfolio level — not the deal level. Master Gambler's Ruin, risk-adjusted value vs expected value, and position sizing as a portfolio decision rather than a conviction signal.
How to allocate reserves under uncertainty, avoid pro-rata traps, and maintain conviction without averaging into losers. Build a disciplined follow-on engine that maximizes portfolio-level EV rather than individual deal optics.
Use the cross-plot decision surface to evaluate every holding continuously. Map companies into Hold, Sell, or Recycle zones using IRR contours — not gut feel. Time decay is real. Every year held must justify itself in IRR terms. Partial exits are a feature, not a failure.
Close the loop between prediction and outcome. Build a calibration system that tests Pv accuracy, P10–P90 interval coverage, and individual investor bias direction. A flat histogram is the goal. Systematic learning is what separates top-quartile firms over time.
The System
Each module connects to the others. Together they form a closed-loop investment system: from choosing the right vertical, to selecting what to back, to realizing returns, to learning and improving.
Who This Is For
Programs launch later this year. Founding members get early access, priority pricing, and preview content from the curriculum before public launch.