It is common practice to identify the number and sources of shocks that move implied volatilities across space and time by applying Principal Components Analysis (PCA) to pooled covariance matrices of changes in implied volatilities. This approach, however, is likely to result in a loss of...

In this paper, we consider simple and easy distributed computing abilities of the statistical system TISAS (TIme Series Analysis Supporting System). TISAS was mainly "'written in the Tcl / Tk language, and was designed for utilizing full merits of a GUI (Graphical User Interface). We add...

We analyse in this article the monthly structure of the Brazilian inflation rate by means of fractionally integrated techniques. This series is characterized by strong government interventions to bring inflation to a low level. We use a testing procedure due to Robinson (1994) which allow us to...

In order to obtain exact distributional results without imposing restrictive parametric assumptions, several rank counterparts of the Dickey-Fuller statistic are considered. In particular, a rank counterpart of the score statistic is suggested which appears to have attractive theoretical...

Kernel smoothing in nonparametric autoregressive schemes offers a powerful tool in modelling time series. In this paper it is shown that the bootstrap can be used for estimating the distribution of kernel smoothers. This can be done by mimicking the stochastic nature of the whole process in the...

A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive time series. We derive its consistency for both local constant and local linear estimators using a derived optimal bandwidth. Further asymptotic analysis suggests a greater...

Testing the cointegrating rank of a vector autoregressive process which may have a deterministic linear trend is considered. Previous proposals for dealing with such a situation are either to allow for a deterministic trend term in computing a suitable test statistic or else remove the linear...