A Methodological model to assist the optimization and risk management of mining investment decisions

Identifying, quantifying, and minimizing technical risks associated with investment decisions is a key challenge for mineral industry decision makers and investors. However, risk analysis in most bankable mine feasibility studies are based on the stochastic modelling of project “Net Present Value” (NPV)which, in most cases, fails to provide decision makers with a truly comprehensive analysis of risks associated with technical and management uncertainty and, as a result, are of little use for risk management and project optimization. This paper presents a value-chain risk management approach where project risk is evaluated for each step of the project lifecycle, from exploration to mine closure, and risk management is performed as a part of a stepwise value-added optimization process.

Factors influencing metal price selection in mining feasibility studies

The mineral price assigned in mining project design is critical to determining the economic feasibility of a project. Nevertheless, although it is not difficult to find literature about market metal prices, it is much more complicated to achieve a specific methodology for calculating the value or which justifications are appropriate to include. This study presents an analysis of various methods for selecting metal prices and investigates the mechanisms and motives underlying price selections. The results describe various attitudes adopted by the designers of mining investment projects, and how the price can be determined not just by means of forecasting but also by consideration of other relevant parameters.

El CIFOT como apoyo a la gestión gubernamental : inconveniente para la inversión minera

La falta de información sistematizada sobre reservas mineras causa desinterés de los capitales extranjeros, que demandan un conocimiento preciso sobre localización de yacimientos y un catastro saneado (con los títulos de propiedad correctos). En este artículo se presenta la experiencia del CIFOT en el trabajo solicitado a tales fines por la Dirección de Minería, denominado Situación de la Información Minera- Provincia de Mendoza, 1993" El objetivo principal fue evaluar la información disponible en la Dirección, procesarla, graficarla y generar cartografía temática a partir del uso de GIS, para ser presentada por las autoridades gubernamentales en Denver, USA, ante diversos inversores del sector. Se logra evidenciar la representatividad de la minería en Mendoza, por departamentos, la distribución de los yacimientos mineros, el estado de cada uno y la infraestructura vial de acceso. Esto permite a la Dirección de Minería implementar un sistema unificado de información minera, tarea que a posteriori es completada por el programa nacional PASMA.

Minería metalífera en Santa Cruz : Empleo y matriz productiva

El presente estudio se propone realizar una caracterización de la minería metalífera en la Provincia de Santa Cruz. Esta actividad comenzó a desarrollarse en esa provincia desde mediados de los años 90 y, hasta la fecha, creció en forma sostenida como consecuencia del cruce de una serie de circunstancias favorables: a) las modificaciones en la legislación, que favorecieron la inversión minera al equiparar en oportunidades a la República Argentina con Chile y el Perú, países con un elevado desarrollo minero gracias a la importante inversión externa directa; b) el potencial minero de la provincia; c) la crisis en el sector lanero -especialmente en la meseta central de la provincia- que llevó a un despoblamiento de los campos de actual explotación minera, lo que redujo la potencial conflictividad entre la minería y la ganadería y facilitó a la nueva actividad la adquisición de propiedades a bajos precios, presentándola, además, como un sector generador de empleo; d) la lejanía de los yacimientos mineros de los centros poblados de la provincia, que favoreció un consenso social superior al verificado en otras regiones del país. En la actualidad, en un contexto de aumento generalizado de los precios internacionales de las commodities, se observa un constante incremento de la actividad minera en la Provincia de Santa Cruz. Ello ha conducido a la incorporación de nuevas tecnologías de producción para la recuperación mineral y a dar impulso a nuevas explotaciones

Minería metalífera en Santa Cruz : Empleo y matriz productiva

El presente estudio se propone realizar una caracterización de la minería metalífera en la Provincia de Santa Cruz. Esta actividad comenzó a desarrollarse en esa provincia desde mediados de los años 90 y, hasta la fecha, creció en forma sostenida como consecuencia del cruce de una serie de circunstancias favorables: a) las modificaciones en la legislación, que favorecieron la inversión minera al equiparar en oportunidades a la República Argentina con Chile y el Perú, países con un elevado desarrollo minero gracias a la importante inversión externa directa; b) el potencial minero de la provincia; c) la crisis en el sector lanero -especialmente en la meseta central de la provincia- que llevó a un despoblamiento de los campos de actual explotación minera, lo que redujo la potencial conflictividad entre la minería y la ganadería y facilitó a la nueva actividad la adquisición de propiedades a bajos precios, presentándola, además, como un sector generador de empleo; d) la lejanía de los yacimientos mineros de los centros poblados de la provincia, que favoreció un consenso social superior al verificado en otras regiones del país. En la actualidad, en un contexto de aumento generalizado de los precios internacionales de las commodities, se observa un constante incremento de la actividad minera en la Provincia de Santa Cruz. Ello ha conducido a la incorporación de nuevas tecnologías de producción para la recuperación mineral y a dar impulso a nuevas explotaciones

Minería metalífera en Santa Cruz : Empleo y matriz productiva

El presente estudio se propone realizar una caracterización de la minería metalífera en la Provincia de Santa Cruz. Esta actividad comenzó a desarrollarse en esa provincia desde mediados de los años 90 y, hasta la fecha, creció en forma sostenida como consecuencia del cruce de una serie de circunstancias favorables: a) las modificaciones en la legislación, que favorecieron la inversión minera al equiparar en oportunidades a la República Argentina con Chile y el Perú, países con un elevado desarrollo minero gracias a la importante inversión externa directa; b) el potencial minero de la provincia; c) la crisis en el sector lanero -especialmente en la meseta central de la provincia- que llevó a un despoblamiento de los campos de actual explotación minera, lo que redujo la potencial conflictividad entre la minería y la ganadería y facilitó a la nueva actividad la adquisición de propiedades a bajos precios, presentándola, además, como un sector generador de empleo; d) la lejanía de los yacimientos mineros de los centros poblados de la provincia, que favoreció un consenso social superior al verificado en otras regiones del país. En la actualidad, en un contexto de aumento generalizado de los precios internacionales de las commodities, se observa un constante incremento de la actividad minera en la Provincia de Santa Cruz. Ello ha conducido a la incorporación de nuevas tecnologías de producción para la recuperación mineral y a dar impulso a nuevas explotaciones

ArcelorMittal: Metals & Mining: Equity Investment Report

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

ArcelorMittal: Metals & Mining – Europe: Equity Investment Report

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Fomento de las inversiones y financiamiento de la minería en América Latina = Investment promotion and financing of mining in Latin America

Incluye Bibliografía

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Multimodal Investment Analysis Methodology, Phase One: The Conceptual Model, 1998

The purpose of this project is to develop an investment analysis model that integrates the capabilities of four types of analysis for use in evaluating interurban transportation system improvements. The project will also explore the use of new data warehousing and mining techniques to design the types of databases required for supporting such a comprehensive transportation model. The project consists of four phases. The first phase, which is documented in this report, involves development of the conceptual foundation for the model. Prior research is reviewed in Chapter 1, which is composed of three major sections providing demand modeling background information for passenger transportation, transportation of freight (manufactured products and supplies), and transportation of natural resources and agricultural commodities. Material from the literature on geographic information systems makes up Chapter 2. Database models for the national and regional economies and for the transportation and logistics network are conceptualized in Chapter 3. Demand forecasting of transportation service requirements is introduced in Chapter 4, with separate sections for passenger transportation, freight transportation, and transportation of natural resources and commodities. Characteristics and capacities of the different modes, modal choices, and route assignments are discussed in Chapter 5. Chapter 6 concludes with a general discussion of the economic impacts and feedback of multimodal transportation activities and facilities.

Structural adjustment and subsistence industry: artisanal gold mining in Ghana

Since the implementation of Ghana's national Structural Adjustment Programme (SAP), policies associated with the programme have been criticized for perpetuating poverty within the country's subsistence economy. This article brings new evidence to bear on the contention that the SAP has both fuelled the uncontrolled growth of informal, poverty-driven artisanal gold mining and further marginalized its impoverished participants. Throughout the adjustment period, it has been a central goal of the government to promote the expansion of large-scale gold mining through foreign investment. Confronted with the challenge of resuscitating a deteriorating gold mining industry, the government introduced a number of tax breaks and policies in an effort to create an attractive investment climate for foreign multinational mining companies. The rapid rise in exploration and excavation activities that has since taken place has displaced thousands of previously-undisturbed subsistence artisanal gold miners. This, along with a laissez faire land concession allocation procedure, has exacerbated conflicts between mining parties. Despite legalizing small-scale mining in 1989, the Ghanaian government continues to implement procedurally complex and bureaucratically unwieldy regulations and policies for artisanal operators which have the effect of favouring the interests of established large-scale miners.

Artisanal gold mining at the margins of mineral resource governance : a case from Tanzania

This article discusses the character of mineral resource governance at the margins of the state in Tanzania and the way artisanal gold miners are incorporated into mineral sector transformation. The landscape of mineral resource exploitation has changed dramatically over the past 20 years: processes of economic liberalisation have heralded massive foreign investment in large-scale gold mining, while also stimulating artisanal activities. Against this background, the article shows how artisanal gold miners are affected by contradictory processes: some have become integrated with state institutions and legal processes, while others, the large majority, are either further excluded or incorporated in ways that exacerbate insecurity and exploitation, underpinned by socio-economic inequalities. These processes are compounded by the actions of large-scale and medium-scale gold mining companies and by poor local governance. It is open to debate whether this will bring improved integration and welfare for artisanal mining communities or new forms of exclusion, although evidence suggests the latter.

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.

Can profitable trading strategies be derived from investment best-sellers?

A glance along the finance shelves at any bookshop reveals a large number of books that seek to show readers how to ‘make a million’ or ‘beat the market’ with allegedly highly profitable equity trading strategies. This paper investigates whether useful trading strategies can be derived from popular books of investment strategy, with What Works on Wall Street by James P. O'Shaughnessy used as an example. Specifically, we test whether this strategy would have produced a similarly spectacular performance in the UK context as was demonstrated by the author for the US market. As part of our investigation, we highlight a general methodology for determining whether the observed superior performance of a trading rule could be attributed in part or in entirety to data mining. Overall, we find that the O'Shaughnessy rule performs reasonably well in the UK equity market, yielding higher returns than the FTSE All-Share Index, but lower returns than an equally weighted benchmark