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Revista de Medio Ambiente y Mineria
Print version ISSN 2519-5352
Abstract
MEDINACELI TORREZ, Rubén. Average annual quote prediction of the main minerals exploited in bolivia, for the period 2014-2024. REV. MAMYM [online]. 2019, vol.4, n.2, pp.58-72. ISSN 2519-5352.
Abstract The mining industry is one of the most important in the country; Therefore, it requires a lot of attention from a scientific and technological point of view. The life of a mining project easily exceeds twenty years, the period of time from the moment in which an exploration campaign verifies the existence of an exploitable mineralized body and the beginning of the exploitation itself can easily, depending on the size of the mineralized deposit , exceed five or ten years. In other words, if today we decide to exploit a mineralized body, the exploitation itself will begin in five to ten years. This means that it is absolutely necessary to estimate or predict quotes and costs for considerable periods of time, ten or twenty years. Therefore, it is important to develop our own prediction models and use them to predict in this case, prices of the minerals that are exploited in the country (Au, Ag and Sn). There are several alternatives to build prediction models for mineral quotes; from complex econometric prediction models to simple models based on their trend analysis. The concept of trend analysis is to adjust a trend line, using regression analysis or time series to historical data of the price of the mineral of interest. This method can often provide a good first estimate of future quotes. Econometric methods of price prediction involve modeling the interrelationships between supply, demand and cost elements from one to more minerals. The present work proposes to build quotation prediction models for the Au, Ag and Sn minerals. In each case a trend analysis will be carried out in addition to proposing an econometric model. Both models will be used to predict the average annual prices of the minerals listed for the 2014-2023 period. Each of the models will be validated and the most convenient for the purpose noted will be recommended
Keywords : prediction; quotations; minerals; Bolivia..