The Research On The Monitoring Warning System Of The Rural Financial Risks In Xinjiang

Xinjiang is the less developed western frontier minority areas as well as the agriculturalbig province, and the development of the rural finance is vital to the development ofagriculture and rural economy. Since China’s reform and opening up, rural finance has madegreat development in Xinjiang, but rural financial ecological imbalance has greatly hinderedthe sustainable development of rural economy in Xinjiang. Therefore, in Xinjiang ruralfinancial risk is discovered early signal of the government’s infancy, which is the financialcrisis to take effective measures to avoid the occurrence of crisis, so as to realize the effectivecontrol of Xinjiang rural financial risk.In this paper, based on the study of Xinjiang rural financial risk in the perspective offinancial ecological environment situation, first of all, in this paper, the rural financial risksand the rural financial ecological theory are researched, then exploring the relationshipbetween rural financial risk and the rural financial ecology, on the basis of focus, this articleanalyzes the ecological environment of Xinjiang rural financial risk factors. Secondly, thispaper uses the statistical early warning and model to analysis the empirical research part.Finally, in the policy research, in view of the research targeted and constructive Suggestionsare put forward.This article investigated Xinjiang rural finance is the ecological environment, and get thefollowing conclusions: First, Xinjiang rural financial ecological environment is not stable andperfect, remains to be further optimized. Second, through the empirical part of the research,this paper suggests that agricultural GDP growth ratio, urban and rural resident income ratio,ratio of agriculture, peasant household savings rate and growth rate of financial supportagriculture are very sensitive indicator of Xinjiang rural financial operation. For the sake ofXinjiang rural financial health running, it is necessary to use risk early warning model foreffective monitoring of the seven indicators.