The capital markets across different economies have always been an extremely debated subject that represents a key point when discussing about the overall degree of performance of any economy. The main purpose of this article is to test the random walk hypothesis for the Romanian stock market...

Over the last years there has been considerable interest in the application of long memory time series models in economics using ARFIMA models. Nowadays, the most popular estimator of the difference parameter in economic applications is that proposed by Geweke and Porter-Hudak (GPH) although has...

In short-term evolution analysis, the economic time series are contamined by different types of noises which need to be erased in order to extract a trend signal. In the last years there has been increasingly developed some methods to estimate unobserved components based on the assumption that...

Several studies have tested for long-range dependence in macroeconomic and financial time series but very few have assessed the usefulness of long-memory models as forecast generating mechanisms. This study tests for fractional differencing in the U.S. monetary indices (simple sum and divisia)...

This paper describes a parameter estimation method for both stationary and non-stationary ARFIMA (p,d,q) models, based on autoregressive approximation. We demonstrate consistency of the estimator for -1/2 d 1, and in the stationary case we provide a Normal approximation to the finite-sample...

In this study we tested the existence of long memory in the the return series for major Central Eastern European and Balkans stock markets, using the following statistical methods: Hurst Exponent, GPH method, Andrews and Guggenberger method, Reisen method, Willinger, Taqqu and Teverovsky method...