| With the acceleration of the pace of financial integration in recent years,the consequences of the bursting of the asset bubble have a greater impact and broader scope.Among them,the impact of the bubble burst in the stock market is more frequent and more destructive than other markets,and may even induces a global financial crisis.In this context,in order to take effective countermeasures to prevent and control the crisis caused by the stock market bubble burst,it is necessary to make timely and accurate judgments on the change of stock market bubble state.Based on the analysis of the singularity point of the stock market index by wavelet analysis,this thesis uses the LPPL model to judge the change of the the stock market bubble state.Firstly,it analyzes the connotation,characteristics and mechanism of the stock market bubble,and discusses the theoretical basis of wavelet analysis and LPPL model.Secondly,after examining the nonlinear and fractal characteristics of the stock market by using BDS test and R/S analysis method,this thesis uses the Mallat algorithm to decompose and reconstruct the stock market index,and then uses the local modulus maximum value detection to detect its singularity point.Finally,this thesis uses the LPPL model to judge the stock market bubble state of each period,and analyzes the reasons from the policy perspective.The empirical results indicate that there are positive bubbles in the stock market during the early period of bubble burst,and when the bubble breaks,there are negative bubbles in the stock market,and this transformation occurs before the bubble burst.After the bubble burst,the stock market bubble first remains a negative bubble state for a period of time,then begins to switch between inverted negative bubbles and inverted positive bubbles.After analyzing the reason,this thesis finds that the occurrence of policy events is closely related to the change of stock market bubble state,and then puts forward some relevant policy suggestions. |
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