Algorithmic Game Theory & Nash Equilibrium Solver for Multi-Class Private Equity
Algorithmic Game Theory & Nash Equilibrium Solver for Multi-Class Private Equity
Equilibria · Open Venture Framework (ovf) — an executable semantics for private-equity contracts. Given a cap table and an exit, it solves the conversion game every preferred class plays against every other, certifies the equilibrium, and reconciles every dollar. Around that core: priced rounds as fixed points, a two-stage governance vote, an Option Pricing Method that refuses the tables it cannot price, and a fund-performance engine whose IRR never picks a root.
------ Solution concept pure ε-Nash equilibrium of the conversion game, certified by an exhaustive unilateral-deviation check; exhaustive 2^n survey for payoff uniqueness Strategic layers position-level conversion game · two-stage Requisite Holders vote · MFN elections resolved continuously Fixed points mixed pre/post-money SAFE rounds as one concave piecewise-affine equation with a uniqueness certificate Valuation Black–Scholes–Merton call spreads over engine-derived breakpoints, backsolve, four DLOM estimators Fund performance certified XIRR (Descartes–Jameson bound + Rolle isolation in log space), KS-PME, Direct Alpha, PME+, Long–Nickels ICM, mPME Evidence 2,211 tests · three independently written exact oracles · adversarial reviews · every refusal is explicit Interfaces Python API (ovf, alias equilibria) · CLI · MCP server for AI agents · OCF v1.2.0 read/write
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