Using the spectral regression and Gaussian semiparametric methods of estimating the long-memory parameter, we test for fractional dynamic behavior in a number of important Japanese financial time series: spot exchange rates, forward exchange rates, stock prices, currency forward premia, Euroyen deposit rates, and the Euroyen term premium. Stochastic long memory is established as a feature of th...

The traditional base state with amendments model usually use the time sequence when choosing the base state to manipulate and it is usually use the extension of time point to represent the time-slot retrieval, which ignores the adjacent feature of the time point in a certain time-slot. The concept of operated base state and operation times is introduce in this paper, in which a base state with ...

This paper reviews the main estimation and prediction results derived in the context of functional time series, when Hilbert and Banach spaces are considered, specially, in the context of autoregressive processes of order one (ARH(1) and ARB(1) processes, for H and B being a Hilbert and Banach space, respectively). Particularly, we pay attention to the estimation and prediction results, and sta...

We present a new approach to generalised autoregressive conditional heteroscedasitic (GARCH) modelling for asset returns. Instead of attempting to choose a speciic distribution for the errors, as in the usual GARCH model formulation, we use a nonparametric distribution to estimate these errors. This takes into account the common problems encountered in nan-cial time series, for example, asymmet...

This paper introduces the class of seasonal specific structural time series models, according to which each season follows specific dynamics, but is also tied to the others by a common random effects. This results in a dynamic variance components model that can account for some kind of periodic behaviour, such as periodic heteroscedasticity, and is tailored to deal with situations when one or a...

In many applications, the duration of an uninterrupted measurement of a time series is limited. However, it is often possible to obtain several separate segments of data. The estimation of an autoregressive model from this type of data is discussed. A straightforward approach is to take the average of models estimated from each segment separately. In this way, the variance of the estimated para...

This paper presents an econometric model that combines macroeconomic time series data with historical series relating to political instability in Israel during the Intifada period, in order to provide a conservative estimate of the extent to which variations in economic performance over time have a political explanation. Political instability is found to have a substantial effect on the cyclica...

The few existing empirical studies of U.S.-Japan trade agreements have relied primarily on descriptive statistics or univariate time series methods. We conduct a more powerful test by evaluating agreements in the context of well-specified econometric models. Consistent with trade theory, import demand is modeled as a cointegrating relationship with income and relative price variables, where a t...

Policy makers and managers sometimes assess the share of research produced by a group (country, department, institution). This takes the form of the percentage of publications in a journal, field or broad area that has been published by the group. This quantity is affected by essentially random influences that obscure underlying changes over time and differences between groups. A model of resea...