Behavioral Heterogeneity and Real-Time Option Pricing: Evidence from S&P 500 Options

This study develops a two-stage behavioral model for real-time option pricing in markets characterized by heterogeneous agents. The framework integrates traders' subjective beliefs about terminal asset prices with their individual execution propensity parameters, which govern the probability of accepting a counterparty's offer. In the first stage, algebraic conditions establish a feasible transaction-price domain based on each participant's beliefs and transaction costs. In the second, a nonlinear optimization process determines reduced price bounds that capture strategic behavior and heterogeneity in execution propensity, thereby generating bid-ask spreads and waiting intervals endogenously. Using S&P 500 Call-option data from 2020 (242,697 contracts), the model is benchmarked against Yoshida's fuzzy-logic (F-L), Black-Scholes and Heston stochastic-volatility frameworks, achieving materially lower pricing errors across all moneyness levels and maturities. Quantitatively, the model reduces average pricing errors by more than 30% relative to benchmark frameworks. The findings demonstrate that behavioral heterogeneity and execution propensity jointly explain option-price deviations and the microstructure of real-time markets. This study contributes to the behavioral-finance literature by integrating real-time microstructure dynamics with heterogeneous beliefs, offering a tractable and empirically validated pricing framework.