The purpose of this paper is to analyze the dynamics of crude oil prices of OPEC and non-OPEC countries using threshold cointegration. To capture the long-run asymmetric price transmission mechanism, we develop an error correction model within a threshold cointegration and CGARCH errors...

This paper introduces a two-step procedure for convex penalized estimation in dynamic location-scale models. The method uses a consistent, non-sparse first-step estimator to construct a convex Weighted Least Squares (WLS) optimization problem compatible with the Least Absolute Shrinkage and...

The ability of Google Trends data to forecast the number of new daily cases and deaths of COVID-19 is examined using a dataset of 158 countries. The analysis includes the computations of lag correlations between confirmed cases and Google data, Granger causality tests, and an out-of-sample...

This paper examines the relationship between the Russian ruble/US dollar exchange rate and global oil prices using autoregressive model with Markovian regime shifts. Empirical analysis on daily data for 2009–2019 shows that exchange rate dynamics is best described by three regimes,...

This is an exploratory study that attempts to identify and provide empirical evidence on the possible determinants of the market capitalisation of the Harare Stock Exchange (HSE) with the view of understanding the development prospects of the HSE and other similar markets. The study used...

This paper studies the sequential sampling scheme as a solution to the problem of aliasing, where the sampling interval is restricted to a minimum allowable value. Sequential sampling is analyzed and it is proved that when the sampling ratio is an integral number, the associated spectral...

The paper focuses on the comparison of the direct and iterated AR predictors for difference stationary processes. In particular, it provides new methods for comparing the efficiency of the two predictors and for extracting the trend from macroeconomic time series using the two methods. The...

We calibrate Markov regime-switching (MRS) models to mean daily spot prices from the EEX market. Our empirical study shows that (i) models with shifted spike regime distributions lead to more realistic models of electricity spot prices and that (ii) introducing heteroskedasticity in the base...

The paper compares one-period ahead forecasting performance of linear vector-autoregressive (VAR) models and single-equation Markov-switching (MS) models for two cases: when leading information is available and when it is not. The results show that single-equation MS models tend to perform...

This paper introduces new methods of estimating Value-at-Risk (VaR) using Range-Based GARCH (General Autoregressive Conditional Heteroskedasticity) models. These models, which could be either based on the Parkinson Range or Garman-Klasss Range, are applied to 10 stock market indices of selected...