Option-implied risk-neutral densities are widely used for constructing forward-looking risk measures. Meanwhile, investor risk aversion introduces a multiplicative pricing kernel between
the risk-neutral and true conditional densities of the underlying asset’s return. This paper proposes a simple local estimator of the pricing kernel based on inverse density weighting. We characterize the asymptotic bias and variance of the estimator and its multiplicatively corrected density forecasts. The estimator with plug-in bandwidths performs well in a simulation study. A local exponential linear variant is proposed to include conditioning variables. We apply our estimator to a demand-based model for S&P 500 index options using net positions data, and attribute U-shaped pricing kernels to heterogeneous beliefs about volatility.