We test for stochastic long memory in the Greek stock market, an emerging capital market. The fractional differencing parameter is estimated using the spectral regression method. Contrary to findings for major capital markets, significant and robust evidence of positive long-term persistence is...

This paper studies the error in forecasting a dynamic time series with a deterministic component. We show that when the data are strongly serially correlated, forecasts based on a model which detrends the data before estimating the dynamic parameters are much less precise than those based on an...

We employ a nonlinear, nonparametric method to model the stochastic behavior of changes in the 90-day U.S. T-bill rate. The estimation technique is locally weighted regression (LWR), a nearest-neighbor method, and the forecasting criteria are the root mean square error (RMSE) and mean absolute...

We test for long memory in 3- and 6-month daily returns series on Eurocurrency deposits denominated in Japanese yen (Euroyen). The fractional differencing parameter is estimated using the spectral regression method. The conflicting evidence obtained from the application of tests against a unit...

We argue that the current framework for predictive ability testing (e.g.,West, 1996) is not necessarily useful for real-time forecast selection, i.e., for assessing which of two competing forecasting methods will perform better in the future. We propose an alternative framework for out-of-sample...