Based　on　the　framework　of　non-parametric　approach,　the　new　jump　variance　and　continuous　sample　path　variance　are　constructed　and　the　jump　variance　is　modeled　by　combining　A-J　jump　detection　statistic.　With　high　frequency　data　from　Shanghai　composite　index,　the　empirical　analyses　are　carried　out　from　four　aspects:　the　characteristics　and　contribution　of　jump　variance,　jump　sizes　and　the　relationship　between　economic　information　and　jump.　It　turns　out　that　the　jump　variance　series　show　leptokurtic,　heavy　tail　and　volatility　clusters;　the　contribution　of　jump　variance　to　whole　variance　nearly　equals　for　different　sampling　frequency;　the　positive　jump　and　negative　jump　are　asymmetric　and　the　adjusted　returns　are　nearly　normal　distribution　by　the　single　jump　adjustments;　the　correlation　between　the　jumps　and　economic　information　release　is　always　positive.　©　2013　IEEE.