This paper applies three universal approximators for forecasting. They are the Artificial Neural Networks, the Kolmogorov-Gabor polynomials, as well as the Elliptic Basis Function Networks. We are particularly interested in the relative performance and stability of these. Even though forecast...

This paper is concerned with univariate noncausal autoregressive models and their potential usefulness in economic applications. In these models, future errors are predictable, indicating that they can be used to empirically approach rational expectations models with nonfundamental solutions. In...

It has been argued that estimating the spectral density function of a stationary stochastic process at the zero frequency (or the so-called long-run variance) is an ill-posed problem so that any estimate will have an infinite minimax risk (e.g., Pötscher 2002). Most often it is a nuisance...

In this paper, we consider estimating copulas for time series, under mixing conditions, using wavelet expansions. The proposed estimators are based on estimators of densities and distribution functions. Some statistical properties of the estimators are derived and their performance assessed via...

We use the HYBRID GARCH model of Chen, Ghysels, and Wang (2009) to predict future volatility at daily horizons using intra-daily returns. The latter requires us to address intra-daily periodic patterns. We propose two approaches and compare their relative merits. The first approach uses raw...

This paper considers VECMs for variables exhibiting cointegration and common features in the transitory components. While the presence of cointegration between the permanent components of series reduces the rank of the long-run multiplier matrix, a common feature among the transitory components...

We propose two nonparametric methods to test the null hypothesis of periodic integration, one based on the variance ratio unit root test of Breitung (2002) and the other on the modified Sargan-Bhargava test developed by Stock (1999). The former does not require specification of short-run...