We study the relation between a comprehensive set of firm characteristics and the entire universe of individual equity option prices. We find that 42 out of 86 characteristics are priced in the option market, in the sense that they significantly explain differences in the implied volatility surface (IVS) across stocks. Motivated by this finding, we model the IVS of a given stock as a function of its characteristics with a local linear random forest. This approach addresses the illiquidity of the equity option market by effectively grouping similar stocks during estimation. Our method outperforms a stock-specific benchmark model out-of-sample and allows us to uncover the nonlinear interactions between characteristics and option prices.