A Comparative Analysis of Rock Fragmentation using Blast Prediction Results

This work presents prediction and optimisation of controllable parameters of drilling and blasting currently used at the Fobinso Pit of Perseus Mining Ghana Limited (PMGL). The mine faces challenges with blast particle sizes produced after primary blasting. The presence of boulders requires secondary fragmentation to further reduce the broken materials to the acceptable sizes, thereby increasing the cost of production. The mechanical properties of the rocks were determined using Protodyakonov Rock Strength Index. The drill and blast parameters were estimated using the Konya and Walter (1990), Principle of Proportionality, and Instituto Geologo Minero de España (IGME) model developed in 1987. The Modified Kuz-Ram model was used to predict and analyse the results of blasting based on the parameters such as spacing, burden, drillhole diameter, charge density, charge per hole, charge length, and powder factor. A comparative analysis of the predicted size distributions of the various models using diameters of 65 mm and 110 mm revealed no significant differences between the size fractions. The Principle of Proportionality produced the best technical and economic indices for blasting. Keywords: Fragmentation, Drilling Parameters, Primary Blasting, Models, Secondary Blastin

Co-movement of real exchange rates in the West African Monetary Zone

In three different ways of lead–lag causal relationship, covariance/correlation and coherence, we apply the wavelets analysis via the Continuous Morlet Wavelet Transform to delineate the significant frequency–time domain lead–lag relationships for the West African Monetary Zone member countries for real US dollar exchange rates and their absolute log returns from January 2001 to April 2015. The results indicate that lead–lag associations at different periodicities vary across the countries. No one country comes off as leading conveniently for both real and absolute returns of the exchange rates. Our results corroborate other evidences of non-convergence of exchange rates in the monetary zone, which hinders the eventual implementation of the single currency in the ECOWAS region

Connectedness of cryptocurrencies and gold returns: Evidence from frequency-dependent quantile regressions

This paper explores the symmetric and asymmetric dependency structure of decomposed return series of Gold and eight cryptocurrencies to establish the hedging and diversification potentials of these asset classes. Daily data spanning 30 April 2013 to 18 April 2019 are employed within the Ensemble Empirical Mode Decomposition and Quantile-in-Quantile regression techniques. Our empirical results provide evidence that cryptocurrencies and Gold can both hedge and diversify for each other at different conditional distributions of their returns. We also find that cryptocurrencies are not purely speculative but can be driven by medium- and long-term fundamentals. In addition, both Gold and cryptocurrencies can be hedge and diversifiers for other traditional asset classes such as crude oil, fiat currencies, and other commodities

Agent-Based Optimization for Truck Dispatching in Open-Pit Mines

The mining industry has long recognized the value of dispatch systems in open pit mines as they reduce load and haul costs. Over the years, researchers have proposed many dispatch systems with various limitations and advantages. The simplest dispatch algorithms are the so called 1-truck-for-N-shovels dispatch strategy. These algorithms are limited by the fact that their objective functions do not consider all the objectives of a mine and cannot be applied to all possible truck-shovel configurations. They are also myopic in nature. However, they are simple and computationally efficient and do not require occasional updates of the upper stage problem as required in multi-stage dispatch algorithms. In this work, an agent-based truck dispatch algorithm that conceptualizes trucks as intelligent agents that make autonomous dispatching decisions to maximize their utility is proposed. The advantages of this algorithm includes utility functions that encapsulate all of management\u27s objectives and agent\u27s with broad situational awareness. They are also more suitable for autonomous trucks. We evaluate the new algorithm against a simple 1-truck-for-N-shovels dispatch strategies using discrete event simulation. The simulation results show that the new utility function has significant advantages over 1-truck-for-N-shovels inspired utility functions. Future work will incorporate adaptive behavior into the model via reinforcement learning algorithm

Analyzing the relationship between global REITs and exchange rates: fresh evidence from frequency-based quantile regressions

This paper contributes to knowledge by investigating the asymmetric dependence structure between the real estate investment trusts (REITs) and currencies from Europe, North America, Asia, and Australasia. We employ the Ensemble Empirical Mode Decomposition (EEMD) technique to decompose price return series into short-term, medium-term, and long-term scales termed as Intrinsic Mode Functions (IMFs) and further examine the asymmetric association between selected country REITs indices and their respective exchange rates (against the dollar) using both Quantile Regression Analysis (QRA) and Quantile-in-Quantile Regression (QQR) techniques. Both QRA and QQR adequately capture the frequency-variant asymmetric link between REITs and exchange rates across different geographical locations. Associations are similar for Australia, Canada, France, and New Zealand as a group and Germany, Hong Kong, Japan, and Singapore as another group in terms of direction, magnitudes, and at which time horizons they occur. Positive and negative associations in Asia are the strongest across quantiles in the long-term. The study reveals the effect of exchange rates on the selected REITs market and the important role played by currencies in the decision-making process of international investors. We contribute to the literature adaptive market hypothesis (AMH) and heterogeneous market hypothesis (HMH). The frequency-based quantile regressions address non-linearity, asymmetry, time-horizon dependent, and non-homogeneous relationships in the markets espoused by both AMH and HMH. Furthermore, we contribute to the literature by employing a noise-reduction technique to the relationship between REITs and exchange rates. This approach reinforces the inefficient market hypothesis in the REITs-macroeconomic nexus. Findings from this study engender new insights into REITs investments in light of exchange rate fluctuations amidst market inefficiencies