Asymptotics for Duration-Driven Long Range Dependent Processes

We consider processes with second order long range dependence resulting from heavy tailed durations. We refer to this phenomenon as duration-driven long range dependence (DDLRD), as opposed to the more widely studied linear long range dependence based on fractional differencing of an $iid$ process. We consider in detail two specific processes having DDLRD, originally presented in Taqqu and Levy (1986), and Parke (1999). For these processes, we obtain the limiting distribution of suitably standardized discrete Fourier transforms (DFTs) and sample autocovariances. At low frequencies, the standardized DFTs converge to a stable law, as do the standardized sample autocovariances at fixed lags. Finite collections of standardized sample autocovariances at a fixed set of lags converge to a degenerate distribution. The standardized DFTs at high frequencies converge to a Gaussian law. Our asymptotic results are strikingly similar for the two DDLRD processes studied. We calibrate our asymptotic results with a simulation study which also investigates the properties of the semiparametric log periodogram regression estimator of the memory parameter

Persistence and cyclical dependence in the monthly Euribor rate

Copyright @ 2011 Brunel UniversityThis paper analyses two well-known features of interest rates, namely their time dependence and their cyclical structure. Specifically, it focuses on the monthly Euribor rate, using monthly data from January 1994 to May 2011. Models based on fractional integration at the long run or zero frequency, although adequately describing the persistent behaviour of the series, do not take into account its cyclical structure. Therefore, a more general cyclical fractional model is considered. Future directions for research in this context are also discussed