Understanding jump dynamics using liquidity measures

Numerous past studies investigate the relationship between volatility and other relevant variables, e.g., asset jumps, liquidity factors. However, empirical studies examining the link between liquidity and jumps are almost non-existent. In this report, we investigate the possible improvement in estimating so-called jump distribution parameters computed from intraday returns by including liquidity measures. More specifically, we first calculate the jump distribution parameters by using classic jump detection techniques in the spirit of Lee and Mykland (2008) and Tauchen and Zhou (2011), and we then use them as our responses in the heterogeneous autoregressive model \citep[e.g.,][]{corsi2009simple}. We examine the in-sample performance of our model and find out that liquidity measures do provide extra information in the estimation of the jump intensity and jump size variation. We also apply the same technique but using one-period-ahead instead of contemporaneous responses; we again find extra explanatory power when the liquidity measures are included.