美联储：期权定价的局部估计：利用市场状态信息改进预测（英文版）

We propose a novel estimation framework for option pricing models that incorporates local, state-dependent information to improve out-of-sample forecasting performance. Rather than modifying the underlying option pricing model, such as the Heston-Nandi GARCH or the Heston stochastic volatility framework, we introduce a local M-estimation approach that conditions on key state variables including VIX, realized volatility, and time. Our method reweights historical observations based on their rel