Robust Constructive Incomplete-Market Finance via SMT (RCIMF-SMT): Subsuming Black-Scholes and Fat Tails into Tensor Phase Transitions

Mathematical finance is severely constrained by idealized assumptions (continuous paths, infinite liquidity) and systematically underestimates extreme Black Swan events due to its reliance on thin-tailed Gaussian distributions. This paper introduces the RCIMF-SMT Framework, subsuming classical financial models into the 6 × 6 × 6 fractal tensor architecture of Seonggil Matrix Theory. By redefining market crashes not as probabilistic outliers but as structural Sashangmugak phase transitions triggered by determinant collapse (det(M_SG) = 0), and enforcing robust hedging via the Heyting operator (ĥ) and Alpha Resonance (φ), we provide a deterministic, computational foundation for incomplete markets, seamlessly deployable on the V87 CUDA engine.