In　order　to　research　RMB　exchange　rate　volatility　under　exchange　rate　elastification,　this　article　selects　the　structure　variables　about　RMB　exchange　rate　volatility　to　forecast　exchange　rate　volatility　by　linear　moving　average　model　(MA),　general　back　propagation　(BP)　network　and　genetic　algorithm　back　propagation　(GABP)　neural　network　model　respectively.　By　comparison,　we　find　that,　in　the　lack　of　flexibility　period,　month-by-month　MA　model　performs　the　optimal　fitting　and　forecasting　efficiency;　along　with　the　exchange　rate　elastification　and　liberalization,　GABP　network　model　done　it　best　both　in　volatility　value　and　volatility　trend.　Exchange　rate　elastification　can　deepen　the　equilibrium　relationship　between　exchange　rate　and　its　structure　variables;　meanwhile,　for　nonlinear　currency　fluctuations,　nonlinear　GABP　model　could　be　better　choice.　©　2011　IEEE.