This paper proposes a Gaussian estimator for nonlinear continuous time models of the short term interest rate. The approach is based on a stopping time argument that produces a normalizing transformation facilitating the use of a Gaussian likelihood. A Monte Carlo study shows that the finite sample performance of the proposed procedure offers an improvement over the discrete approximation metho...

In this paper we apply the wavelets methodology to the analysis of the comovements of for some MENA countries from June 1997 until March 2005. We decompose weekly stock market returns into di¤erent time scale components using the non-decimated discrete wavelet transform and then analyze the relationships among these variables at the di¤erent time scales. Keywords : Stock market returns, Wavelet...

The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution illustrates their usefulness in predicting the downside risk of financial assets in the context of mode...

We perform a series of Monte Carlo experiments in order to evaluate the impact of data transformation on forecasting models, and ̄nd that vector error-corrections dominate di®erenced data vector autoregressions when the correct data transformation is used, but not when data are incorrectly tansformed, even if the true model contains cointegrating restrictions. We argue that one reason for this ...

This paper studies the information content of some Ifo indicators. In particular, we investigate whether two Ifo indicators, one on the current business situation, the other on current production development, provide information on revisions of German industrial production. A new feature of our analysis is the construction and use of a real-time dataset. We conclude that the Ifo indicators play...

This paper reviews the analysis of the threshold autoregressive, smooth threshold autoregressive, and Markov switching autoregressive models from the Bayesian perspective. For each model we start by describing a baseline model and discussing possible extensions and applications. Then we review the choice of prior, inference, tests against the linear hypothesis, and conclude with models selectio...

Multiresolution wavelet analysis is a natural way to decompose economic time series into components of various frequencies: long-run trend, business-cycle component, and high frequency noise. This paper illustrates the method on real GNP and inflation. The business-cycle component of the wavelet-filtered series closely resembles the series filtered by the approximate bandpass filter (Baxter and...

t his paper investigates the asymmetric behavior of inflation. we use logistic smooth transition autoregressive (lstar) model to characterize the regime-switching behavior of iran’s monthly inflation during the period may 1990 to december 2013. we find that there is a triple relationship between the inflation level, its fluctuations and persistence. the findings imply that the behavior of infla...

We address the question of unemployment hysteresis within the context of ARFIMA models. Our results suggest that in the post-1973 era, hysteresis is considerably less of a stylized fact for the unemployment rates of key OECD economies. JEL Categories C22, E30 Please address all correspondence to: Philip Rothman, Department of Economics, Brewster * Building, East Carolina University, Greenville,...

In this paper we generalize the KPSS-type test to allow for two structural breaks. Seven models have been de…ned depending on the way that the structural breaks a¤ect the time series behaviour. The paper derives the limit distribution of the test both under the null and the alternative hypotheses and conducts a set of simulation experiments to analyse the performance in …nite samples. Keywords:...