Decomposing the Theta Cliff: A SIMDEC Analysis of Asymptotic Time-Decay in Long-Call Options with Intraday Empirical Validation

Source abstract

Previous research has shown sector-conditional asymmetry in implied volatility levels and in option returns. However, no prior work has parameterized that asymmetry at the effective-theta layer in a form that fires a non-discretionary rule trigger. This study supplies that parameterization, its formulation, the first observation, and the corpus evidence. An effective theta is defined as Θe=αs,r⋅ΘBS, where ΘBS is the standard Black-Scholes (BS) theta and αs,r is a sector- and regime-conditional scaling factor. A SIMDEC decomposition is used to partition the input space and to determine the corner where α matters most. The use of SIMDEC renders all AI-created solutions free of hallucination and fully explainable. A “first observation” arising from a three-position long-call cohort traversing terminal decay is deployed using eleven intraday snapshots tracked on the trajectory at primary-source resolution. The cohort behaviour matches the α parameterisation to existing market conditions. To empirically evaluate the effectiveness of the approach, a SIMDEC L2 corpus from the same deployment supplies population-level support across 12 sectors and a three-tier quality stratification. The L2 corpus is the output of the THETA AI/ML pipeline – a multi-architecture deep-learning inference system that treats SIMDEC joint-state partitioning and Sobol variance decomposition as complementary interpretability inputs, with the regime classifier carrying the labels and the composite quality scorer carrying the stratification. The mathematical formulation and overall analysis of the asymmetry in the effective-theta provides a “next level” contribution to traditional option methodology.