Our objective is volatility forecasting, which is core to many risk management problems. We provide theoretical explanations for (i) the empirical stylized fact recognized at least since Taylor (1986) and Ding, Granger, and Engle (1993) that absolute returns show more persistence than squared...

This paper bridges the gap between traditional ARCH modelling and recent advances on realized volatilities. Based on a ten-year sample of five-minute returns for the ECU basket currencies versus the US dollar, we find that the realized volatilities constructed from the summation of the...

We propose a seasonal cointegration model (SECM) for quarterly data which includes variables with different numbers of unit roots and thus needs to be transformed in different ways in order to yield stationarity. A Monte Carlo simulation is carried out to investigate the consequences of...

This paper develops an improved test of economic convergence or divergence using time series methods by introducing nonlinear trends in the form of logarithmic trend functions into the vector error correction model. The usefulness of the method is illustrated in an analysis of the growth pattern...

A dynamic time series LInear Structural RELation (LISREL) model is proposed for the analysis of stationary multivariate time series. The model is suitable not only for macro models, but also for panel data models. The implied covariance matrix is derived and it may be used in exact maximum...