  The main purpose of this work is to examine the behavior of the implied
volatility smiles around jumps, contributing to the literature with a
high-frequency analysis of the smile dynamics based on intra-day option data.
From our high-frequency SPX S\&P500 index option dataset, we utilize the first
three principal components to characterize the implied volatility smile and
analyze its dynamics by the distribution of the scores' means and variances and
other statistics for the first hour of the day, in scenarios where jumps are
detected and not. Our analyses clearly suggest that changes in the volatility
smiles have abnormal properties around jumps compared with the absence of
jumps, regardless of maturity and type of the option.
