Research On Volatility Persistence And Co-persistence In Fractal Financial Market

Volatility persistence is found in many financial time series, the method of modeling volatility persistence is an effective instrument from the point of dynamic. With the opening of the capital markets of the world ,the relation among capital markets in different countries is more and more closer ,and the relativity is on rising trend, accordingly ,the research on the persistence and co-persistence among multivariate time series is of great importance to risk management of investors. Because fractal theory can accruately describe the nonlinear dynamic of economic behavior , it is necessary to introduce fractal theory into research of persistence and co-persistence of volatility.In this dissertation, the writer concluds the popular conditional heteroskedasticity models in the world, points out the characters and limits of these methods.. Based on fractal market theory which represents long memory, the writer makes an improvement on existed method of testing long memory persistence and presents spectral-likelihood estimation method of the FIGARCH model. In order to research multivariate FIGARCH ,the writer extends the concept of co-persistence ,brings forward the method of estimating univariate and multivariate FIGARCH, and the spectral method of testing co-persistence, which is the core of this dissertation. Furthermore , the writer extends common concept of cointegeration to one with conditional heteroskedasticity. At last ,the writer tests the model and method discussed above with date of Shanghai and Shenzhen stock markets to show the effectivenes.