This paper examines the relationships between economic growth , energy consumption, trade openness and carbon dioxide emissions for the period 1970-2009 in case of Portugal. In doing so, we use a time series (OLS estimator, the regression with Newey -West standard errors, and ARMA model). We...

Price movement in the electricity market can be viewed as a nonlinear and dynamic system, exhibiting significant chaotic and multiscale characteristics. To conduct more accurate analysis and forecasting, this paper proposes a new Curvelet denoising based algorithm to analyze these...

Econometric issues in the estimation of persistence in macroeconomic time series are considered. In particular, the relative merits of estimates based on ARMA models, ARFIMA models and nonparametric procedures are investigated. It is shown that ARFIMA models are inappropriate for the purpose of...

This paper presents a new method for computing the theoretical autocovariance function of an autoregressive-moving average model. The importance of the reesult is that it yields two interesting results: (1) a closed form solution is derived in terms of roots of the autoregressive polynomial and...

This paper considers forecasting the conditional mean and variance from an ARMA model with GARCH in mean effects. Expressions for the optimal predictors and their conditional and unconditional MSE's are presented. We also derive the formula for the covariance structure of the process and its...

This paper considers tests of parameters instability and structural change with known, unknown or multiple breakpoints. The results apply to a wide class of parametric models that are suitable for estimation by strong rules for detecting the number of breaks in a time series. For that, we use...

To improve the forecasting accuracy of crude oil price with deeper understanding of the market microstructure, this paper proposes a wavelet decomposed ensemble model. The proposed model follows the Heterogeneous Market Hypothesis that assumes the unstationarity and dynamic changing nature of...

We propose an estimation method that circumvents the path dependence problem existing in Change-Point (CP) and Markov Switching (MS) ARMA models. Our model embeds a sticky infinite hidden Markov-switching structure (sticky IHMM), which makes possible a self-determination of the number of regimes...

Value at risk, an effective measurement of financial risk, can be used to forecast the risk associated with oil price movements. In this paper, we propose an improved Historical Simulation Approach, EDFAAF, which is based on a former approach, HSAF. By comparing it with the HSAF approach, we...

In this paper we investigate the impact of data revisions on forecasting and model selection procedures. A linear ARMA model and nonlinear SETAR model are considered in this study. Two Canadian macroeconomic time series have been analyzed: the real-time monetary aggregate M3 (1977-2000), and...