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

具有结构变化的平稳和非平稳经济时间序列分析

基本信息

批准号：
14330005
负责人：
MAEKAWA Koichi
金额：
$ 4.67万
依托单位：
Hiroshima University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2002
资助国家：
日本
起止时间：
2002 至 2004
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-14330005/
关键词：
Structural Change ARCH Unit root Jump diffusion model High frequency date of stock price CUSUM test Wavelet analysis Marked point process Normal Inverse Gaussian分布 Generalized Hyperbolic 株価収益率日経225 ジャンプ拡散過程 Bipower test GARCHモ

项目摘要

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.

（1）对I（1）和I（0）模型提出了一种估计变结构时间序列回归中断点的方法。通过仿真表明，该方法优于已有的方法，具有上级的优点。(2)We提出了一种对方差方程结构变化的检验方法，并给出了该检验方法的渐近分布。我们还通过模拟展示了我们的测试的性能，并将测试应用于日元/美元汇率。（3）在对经济时间序列进行结构变化分析时，经常会遇到一些看起来是跳跃而不是结构变化的情况。所以我们吸引了跳跃扩散过程。我们应用了Kou跳跃扩散模型和Barndorff-Nielsen检验以及谢泼德检验。结果发现，在许多股票价格过程中存在跳跃。(4)We对日本股市的高频数据进行了处理。并发现了数据在一天内的内在运动，如季节变化、跳跃等。我们应用了一个标记点过程来模拟这样的数据。通过仿真研究比较了几种模型的性能。(5)We将小波分析应用于包括股票数据在内的经济数据，发现小波分析在经济时间序列分析中比参数模型分析更有效、更灵活。

项目成果

期刊论文数量（56）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

JUMP DIFFUSION MODELS FOR JAPANESE STOCK MARKET

DOI：
发表时间：
2005
期刊：
影响因子：
0
作者：
K. Maekawa;Sangyeol Lee;Higashi Hiroshima;Takayuki Morimoto;Ken-ichi Kawai
通讯作者：
K. Maekawa;Sangyeol Lee;Higashi Hiroshima;Takayuki Morimoto;Ken-ichi Kawai

最小マルチンゲール測度の下での高頻度データを利用したオプション価格付け

最小鞅测度下使用高频数据的期权定价