| Budget Amount *help |
¥3,070,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥270,000)
Fiscal Year 2007: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2006: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2005: ¥1,000,000 (Direct Cost: ¥1,000,000)
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| Research Abstract |
(1) In nonparametric estimation of term structures of interest rates from traded bond data, it is empirically well-known that approximating forward rate often yields better result. The problem of this approach is, however, that the use of generalized cross-validation cannot be justified to choose regularization parameters. In this project, we established a version of generalized information criteria (GIC) that holds theoretical validity in the determination of regularization parameter. (2) We compared the performance of various types of GARCH models and multivariate GARCH models in terms of the coherency of downside risks, especially Value at Risk (VaR). Given the parameters estimated, we performed prediction simulation and compared the empirical exceedance rate with nominal size through a binomial test. Our conclusion is that Dynamic Conditional Correlation model performs best, together with its parsimonious parametric form. (3) Estimation of unobserved components time series models with intervention terms are studied. Data come from animal dose administration testing. These are time series data such as systolic blood pressure, diastolic blood pressure, heart rate and so on. We considered a time series model to decompose observation into trend, stationary autoregressive part and an exponential type intervention term, which enabled us to estimate acute toxicity through model selection. (4) Aiming disclosure of the research results to the public, online learning system on the web based time series analysis software was studied.
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