The purpose of this work is to study the statistical properties of the MDD for stochastic processes characterized by the stylized facts of real financial time series. The numerical results obtained using a Monte Carlo code are firstly validated against the analytical predictions available within...

The problem of multicollinearity in the assessments of coefficients is well established. However, it is rarely researched in the estimations of macroeconomic variables and economic performance of developing countries. Predicatively, it has impacts on the estimations of coefficients that should...

Ordinary least squares regression residuals have a distribution that is dependent on a scale parameter. The term 'Studentization' is commonly used to describe a scale parameter dependent quantity U by a scale estimate S such that the resulting ratio, U/S, has a distribution that is free of from...

A new quantile regression estimator is developed and it is shown to be consistent and asymptotically normal. The estimator is based on estimating functions to which one can obtain consistent roots by finding the minimax of a certain deviance function. This function is conveniently constructed to...

This paper proposes a new time-varying parameter regression called the autoregressive conditional parameter (ACP) model. The model allows for time-varying conditional parameters such as the regression coefficients (beta coefficients), mean/intercept, variance, duration, skewness and kurtosis. In...

Traditional specifications of export equations incorporate foreign demand as a demand pull factor and the real exchange rate as a relative price variable. However, such standard export equations have failed to explain the export performance of euro area countries during the crisis period. In...

Traditional specifications of export equations incorporate foreign demand as a demand pull factor and the real exchange rate as a relative price variable. However, such standard export equations have failed to explain the export performance of euro area countries during the crisis period. In...

The research used a long memory or Autoregressive Fractionally Integrated Moving Average model to study and forecast crude oil prices using weekly West Texas Intermediate and Brent series for the period 15/5/1987 to 20/12/2013. Fractional differencing Methods such as Local Whittle Estimator and...

Predictive regressions are linear specifications linking a noisy variable such as stock returns to past values of a more persistent regressor with the aim of assessing the presence of predictability. Key complications that arise are the potential presence of endogeneity and the poor adequacy of...

This paper describes a modelling methodology for multivariate stochastic processes. The concept of multiple causality is discussed and a procedure to detect multiple causality is suggested. The data of a major Canadian supermarket is analyzed and a multivariate autoregressive model for this...