| Abstract: | We investigate jump memory using an extensive database of short‐term S&P 500 index options. Jump memory refers to the attenuation of the implied jump intensity and magnitude parameters following a crash event. We use a genetic algorithm to obtain a time series of implied parameter estimates and posit behavioral and rational explanations for parameter attenuation following a crash event. We find that a nested form of the jump‐diffusion model sharpens the remaining parameter estimates and has a negligible effect on pricing accuracy. |
