Analysis of stationary ans non-stationary economic time series with structural changes

点击翻译按钮获取中文摘要

Our main research results are as follows :(1)We proposed a method of estimating break points in a time series regression with structural changes for I(1) and I(0) model By simulation it is shown that our method is superior to the existing methods.(2)We proposed a CUSUM test for structural change in variance equation in ARCH(∞)model and derived the asymptotic distribution of the test. We also showed performance of our test by simulation and applied the test to Yen/Doller exchange rate.(3)Through structural change analysis of economic time series we often encountered cases which seemed to have jump rather than structural changes. So we attracted jump diffusion process. We applied Kou's jump diffusion model and Barndorff-Nielsen and Shepard test for null of no jump. As the result we found that in many stock price processes there were jumps.(4)We dealt with high frequency data of Japanese stock data. and found inherent movement of the data such as seasonal change, jump, and so on within a day. We applied a marked point process to model such data. We compared performance of several models by simulation study.(5)We apply wavelet analysis to economic data including stock data and found that wavelet analysis were effective and more flexible than parametric model analysis in economic time series analysis.