For over a decade, nonparametric modelling has been successfully applied to study nonlinear structures in financial time series. It is well known that the usual nonparametric models often have less than satisfactory performance when dealing with more than one lag. When the mean has an additive...

In this paper we introduce a bootstrap procedure to test parameter restrictions in vector autoregressive models which is robust in cases of conditionally heteroskedastic error terms. The adopted wild bootstrap method does not require any parametric specification of the volatility process and...

We propose a method of modeling panel time series data with both inter- and intra-individual correlation, and of fitting an autoregressive model to such data. Estimates are obtained by a conditional likelihood argument. If there are few observations in each series, the estimates can be...

Bootstrap confidence intervals for impulse responses computed from autoregressive processes are considered. A detailed analysis of the methods in current use shows that they are not very reliable in some cases. In particular, there are theoretical reasons for them to have actual coverage...

This paper develops a new econometric tool for evolutionary autoregressive models where the AR coefficients change smoothly over time. To estimate the unknown functional form of time-varying coefficients, we propose a mdified local linear smoother. The asymptotic normality and variance of the...

This paper suggests a general functional-coefficient regression model in a form of ARX time series model. Contrast to the common threshold variable in the previous works, our model allows each coefficient to possess a different threshold variable and can cover a wide range of nonlinear dynamic...

In a complete financial market every contingent claim can be hedged perfectly. In an incomplete market it is possible to stay on the safe side by superhedging. But such strategies may require a large amount of initial capital. Here we study the question what an investor can do who is unwilling...

In this note the unobserved component approach underlying the software package SEATS is compared with the Beveridge-Nelson type of decomposition for seasonal time series. The main strength of the SEATS approach lies in the appealing model formulation and the careful specification and adjustment...

We emphasize the importance of properly identifying the long-run relations underlying the monetary model of the exchange rate. The separate estimation of long-run money demands leads to a "structural" error correction equation which allows an interpretation of the various channels affecting the...