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The Russian economy is emerging, meaning that natural resources play a dominant role in economic development. Given the considerable volatility in resource prices, we investigate the volatility spillovers among policy uncertainty, international oil prices, exchange rate, stock index and metal prices covering the period of 2 July 2008 to 15 May 2020 for the Russian economy applying Dynamic Connectedness based on Time-Varying Parameter Vector Autoregression (TVP-VAR). Our empirical investigation demonstrates that gold price, Russian policy uncertainty, oil price and stock index are net volatility contributors, whereas palladium, platinum, silver and exchange rate are net volatilities receivers. Market capitalisation and silver market are found to be the highest net contributor and net receiver, respectively. The palladium appears as a net volatility receiver initially, just after the global financial crisis. The Russian economic policy uncertainty appears to be the dominant volatility contributor from 2008 to 2014, but onward it turned to be a net volatility receiver. Over the year 2014, gold price was the prominent volatility contributor to another market when the oil price dropped significantly. The total connectivity of the markets are highly anchored with several exogenous shocks, including economic sanction, adoption of floating exchange rate, oil price plunge. Our empirical findings provide several policy implications to portfolio managers and Russian regional stakeholders. © Sohag K., Husain S., Chukavina K., Al Mamun Md Text. 2022. Russian Foundation for Basic Research, РФФИ; Iran National Science Foundation, INSF The article has been prepared with the support of the grant of RFBR and INSF, code: 20-510-56021 “Modeling the future of Oil Demand and Fiscal Sustainability: Evidence from Iran and Russia”.

Considering that the development of science and technology depends on metal support, the EU, USA, and China have issued a critical metal list on the development report. However, the scarce and important mineral deposits on a global scale will not be enough to meet the huge needs of economic development in the future. Many fields such as renewable energy, high-performance computing, and AI all require critical metals as essential supports. A proper price regulation of such important metals will contribute to the fair price power on the international market. In this paper, the pricing history and strategy of critical metal support are fully studied and discussed. Since China has become a major consumer country, China should gain fair price power in the market of important metals.

Accurate metal price forecasting is the precondition for optimal and sustainable mine production planning. This paper combined two methods for time series analysis. The developed model represents the combination of the Grey System Theory and a Stochastic differential equation. More precisely, we added stochastic term to the first-order whitenization differential equation. Solution of this equation represents the time response function which is capable of creating artificial evolving paths of the metal price. The simulation process resulted in a distribution and adequate expected value at every single point. Further, model efficiency was increased by adding residuals modeled by the Singular Spectrum Analysis method. The model was tested on the monthly lead metal price series. Mean absolute percentage error is 4.37% and the model can be classified as a high-performance model.

This paper tests the hypothesis on the presence of common factors in the dynamics of the Eurasian Economic Union (EAEU) countries’ macroeconomic indicators. As the most important factor, the common dynamics of commodity prices in world markets was chosen. We identified key channels of the transmission of commodity price shocks for EAEU economies. These transmission channels include both direct transmission channels, connected with the terms of trade, and indirect channels. The latter ones include labour migration between EAEU countries, money transactions by migrants, high trade linkages between EAEU countries, and preferential pricing for energy resources. The empirical part of the paper studies the influence of commodity prices on EAEU countries’ macroeconomic indicators. We have proposed a factor autoregressive model. Based on this model, we have identified the first principal component price movements in oil, natural gas, aluminum, copper, steel, gold and wheat. The first principal component explains 75 % of oil and gas price growth rate variation, 45 % of the copper price growth rate variation, and more than 25 % of the variation of other series. Further, we used VAR model to estimate the influence of the first principal component on the EAEU countries’ GDP, consumption and investment dynamics. The results showed the significant positive effect of commodity prices growth in all EAEU members. We also revealed a number of shock transmission features. For example, price shock affected Russian economy through the income effect, while the same shock affected Armenian economy through the direct output stimulation. Our results may be useful for the coordination of the economic policy and business cycles stabilization amongst EAEU countries.

Mining is the process of extracting a naturally occurring material from the earth to derive a profit. Whether the company make a profit or not depends on many economic parameters, among which the most important are the metal prices on the world market and realized operating costs in the process of exploitation. This work presents the influence of copper price change and value of operating costs on the generated cash flows, i.e. profit, in the case of the open pit South Mining District, which operates within the Copper Mine Majdanpek, Serbia.

This paper tests the hypothesis on the presence of common factors in the dynamics of the Eurasian Economic Union (EAEU) countries’ macroeconomic indicators. As the most important factor, the common dynamics of commodity prices in world markets was chosen. We identified key channels of the transmission of commodity price shocks for EAEU economies. These transmission channels include both direct transmission channels, connected with the terms of trade, and indirect channels. The latter ones include labour migration between EAEU countries, money transactions by migrants, high trade linkages between EAEU countries, and preferential pricing for energy resources. The empirical part of the paper studies the influence of commodity prices on EAEU countries’ macroeconomic indicators. We have proposed a factor autoregressive model. Based on this model, we have identified the first principal component price movements in oil, natural gas, aluminum, copper, steel, gold and wheat. The first principal component explains 75 % of oil and gas price growth rate variation, 45 % of the copper price growth rate variation, and more than 25 % of the variation of other series. Further, we used VAR model to estimate the influence of the first principal component on the EAEU countries’ GDP, consumption and investment dynamics. The results showed the significant positive effect of commodity prices growth in all EAEU members. We also revealed a number of shock transmission features. For example, price shock affected Russian economy through the income effect, while the same shock affected Armenian economy through the direct output stimulation. Our results may be useful for the coordination of the economic policy and business cycles stabilization amongst EAEU countries. © 2018 Institute of Economics, Ural Branch of the Russian Academy of Sciences. All rights reserved. Проанализирована гипотеза о наличии общих факторов в динамике основных макроэкономических показателей государств - членов Евразийского экономического союза. Предложена модель факторной авторегрессии, на основе которой была выделена главная компонента динамики цен на нефть, газ, алюминий, медь, сталь, золото и зерно. Проведена оценка влияния изменений главной компоненты цен ресурсных товаров на ВВП, инвестиции и потребление государств.

There are typically many of variables, which are directly or indirectly associated with the value of underground mine project. Having the ability to plan for uncertainties of input variables is increasingly recognized as critical to longterm mining project success. Large capital intensive projects, such as those in the mineral resource industry, are often associated with diverse sources of both internal and external uncertainties. One of the most external influencing uncertainties is related to the future states of metal price. There are many methods which are applied to forecast the future metal prices, but Mean Reversion Process is one of the most applying methods. This paper analyzes the possibility of using of Grey System Theory to metal price forecasting by examining the correlation between results obtained by these two methods. Intra-class Correlation Coefficient is used as a measure of reliability.

El presente estudio desarrolla un particular análisis que abarca cuatro periodos sobre la evolución e implicancias de la actividad minero metalúrgica y su comercialización. El primer periodo normado y regulado por el código de minería de 1950, el cual orientó e impulsó de manera liberal la inversión en minería de capitales principalmente norteamericanos, un segundo periodo considerado entre los años (1968-1980), etapa durante la cual el estado asumió el rol de promotor, ejecutor y líder de la actividad minero metalúrgica y su comercialización de forma monopólica en cumplimiento de la Ley general de minería 18880. Un tercer periodo desde 1980-1990, el cual involucra tanto al segundo gobierno del presidente Femando Belaunde como al primer gobierno de Alan García, etapa durante la cual se mantuvo el papel del estado en lo referente a su accionar como promotor y líder de la actividad minero metalúrgica, variando únicamente su rol monopólico en la comercialización de la producción minera. Un cuarto y último periodo que se encuentra vigente, caracterizado por la privatización de las empresas mineras que eran de propiedad del estado con lo cual se extingue su accionar en la compraventa de minerales, concentrados, fundidos y refinados, regresando en la práctica a esquemas de explotación minera y comercialización similares a las fomentadas por el código de minería de los años cincuenta. Con la aplicación en extremo de políticas económicas de promoción a la inversión en minería de carácter liberal, no se tiene un control/fiscalización de la real valorización de la producción minero metalúrgica y su consecuente comercialización, lo cual estaría permitiendo prácticas de subvaluación y sobrevalorización (transferencia de precios), así mismo se limita la generación de ahorro interno dirigido a inversiones orientadas a la búsqueda de un mayor valor agregado del producto minero, dado que la mayor parte de la inversión minera obedece y depende de capitales foráneos., This study develops a particular diagnosis that covers four periods of the evolution and implications of mining and metallurgical activity and marketing. The first period regulated by de mining code of 1950, which guided and impetus so liberal mining investment capital mainly American, a second period by the years 1968-1980, period during which the state assumed the role of promoter, performer and leader of the mining and metallurgical activity and marketing of monopoly in compliance with the General Mining Law 18880. A third period from 1980-1990, involving both the second administration of President Fernando Belaunde as first government of Alan Garcia, a stage during which remained the state´s role in relation to activity as a promoter and leader of mining activity, metal, varying only their role in the marketing monopoly of mining production. A fourth and final period is in effect, characterized by privatization of mining companies that were owned by the state thus extinguished their actions in the sale of ores, concentrates, melted and refined in practice back schemes mining and marketing similar to those promoted by the mining code of the fifties.

The transition from open pit to underground mining involves drastically changes in the production system. The equipment for underground mining will change as well as the logistics and the transportation system. Demands of rock stability and control will also change in nature and in equipment needed. At the same time the large investments in underground infrastructure and equipment require short lead times to maintain a high cash flow for the companies. Without proper planning many problems can arise influencing the production flow. Therefore it is essential to have detailed planning and modeling before reaching the transitional depth of the mine. Computer software like Surpac can be a suitable tool for simultaneously planning of both the open pit and the underground mining operation.This paper presents some experiences from Björkdal Gold mine, one of the earliest and largest Gold mines in Scandinavia. The paper presents the mine and how the transition from surface to underground mining has been handled and optimized. Godkänd; 2012; 20130521 (ysko)

One critical factor in open pit mining projects is the estimation of the recoverable reserves. The reason for this is that at the valuation stage there is a lack of information about future metal prices and production costs. Consequently, the estimation of the recoverable reserves needs to be done based on a fixed break-even cut-off grade (BECG), in which fixed expected metal prices and production costs are assumed throughout the operating life of the mine (OLM). In this paper, an alternative technique for estimating the recoverable reserves of an open pit mining project is presented and explained in detail. The main characteristic of this technique is that it estimates the recoverable reserves of the project using mining costs as reference: this is done due to the fact that mining costs are easier to model than metal prices. Another important characteristic of this technique is that it uses the uncertainty of the geology of the orebody, given by simulations of the deposit, to make final strategic decisions, such as the selection of the operating life of the mine and the optimal production rate, which minimise the risk of not achieving future production targets while maximising the upside potential of future rewards. As it will be shown, the final outcome of the proposed technique is the generation of a robust open pit design, that include cutbacks and ultimate pit limits, called the marginal open pit mine design (MOPMD). One characteristic of the MOPMD is that, at each production period, it will be characterised by their respective geological uncertainty, given as probability distributions of ore, waste and metal quantities, and by marginal economical project indicators, such as cut-off grades and metal prices, among others. The details follow in the paper.