Before revision:  Namely, we use the realized volatility, bipower variation, two-scale realized volatility, realized kernel and jump wavelet two scale realized volatility. We find that in-sample as well as out-of-sample performance of the model significantly differs based on the realized measure used.
After revision:  Our results show that inclusion of jumps and realized measures robust to noise improves forecasting ability of the model significantly differs based on the realized measure used.