This paper uses a new nonparametric realized volatility model by summing intraday squared returns to explain the discrete jumps and then estimates whether the jumps are significant or not according to derived jump statistics. In particular, this paper includes the periodicity filters of volatility and then analyzes and compares the recent realized discrete jump volatility of US SPC500 returns using the ultra-high frequency five minute returns spanning the period from January 2000 through September 2010 during which volatility was extremely large after year 2009. In the application to the US SPC500 stock price, the empirical estimates show that when we do not include the periodicity filters of volatility such as MAD, Short Half Scale and WSD using ROWV and ROWQ, the five minute returns have the jump probability that there is at least one significant jump per two or three days. When we consider the periodicity filters of volatility, the five minute returns of US SPC500 stock have a little bit smaller jump probabilities. When we include Max outlyingness in the jumps but do not include the filters such as MAD, Short Half Scale and WSD, the five minute returns of US SPC500 stock have the discrete jumps in five or six days. But when we include the volatility filters such as MAD, Short Half Scale and WSD they have the discrete jumps in nine or ten days during this the period from January 2000 through September 2010.