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Keywords:

  • G13

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.