This paper demonstrates that long memory leads to spurious rejection of the linearity hypothesis, when a STAR specification constitutes the alternative.

Many high frequency economic or financial time series display two empirical characteristics: high kurtosis and positive autocorrelation in the centred and squared observations. The first- order autocorrelation is typically low, and the autocorrelation function decays slowly. These series are...

This paper examines the predictability memory of fractionally integrated ARMA processes. Very long memory is found for positively fractionally integrated processes with large positive AR parameters. However, negative AR parameters absorb, to a great extent, the memory generated by a positive...

Since the true nature of a time series process is often unknown it is important to understand the effects of model choice. This paper examines how the choice between modelling stationary time series as ARMA or ARFIMA processes affects the accuracy of forecasts. This is done, for first-order...

This paper shows how a simple univariate stationary nonlinear process has an autocorrelation function suggesting that the underlying process has a long memory, although that is not the case. The conclusion is that just considering linear properties of a process may be misleading.

In this paper two techniques, long memory and panel data models, are combined in order to increase the power of unit root tests. The power is shown to be always better against fractional alternatives and usually against autoregressive alternatives. The test is then used to reanalyze data sets...

In this paper we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in a sample space. We study the performance of our tests by...

This paper studies a class of Markov models which consist of two components. Typically, one of the components is observable and the other is unobservable or 'hidden'. Conditions under which (a form of) geometric ergodicity of the unobservable component is inherited by the joint process formed of...

In this paper, a unified framework for testing the adequancy of an estimated EGARCH model is presented. The tests are Lagrange multiplier or Lagrange multiplier type tests and include testing an EGARCH model against a higher-order one and testing parameter constancy. Furthermore, various...

In this paper we introduce the Smooth Permanent Surge [SPS] model. The model is an integrated non lineal moving average process with possibly unit roots in the moving average coefficients. The process nests the Stochastic Permanent Break [STOPBREAK] process by Engle and Smith (1999) and in a...