Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.

Forecasting Intraday Stock Price Trends with Text Mining Techniques

In this paper, we describe NewsCATS (news categorization and trading system), a system implemented to predict stock price trends for the time immediately after the publication of press releases. NewsCATS consists mainly of three components. The first component retrieves relevant information from press releases through the application of text preprocessing techniques. The second component sorts the press releases into predefined categories. Finally, appropriate trading strategies are derived by the third component by means of the earlier categorization. The findings indicate that a categorization of press releases is able to provide additional information that can be used to forecast stock price trends, but that an adequate trading strategy is essential for the results of the categorization to be fully exploited.

New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^

Romanian glocalization : Case study on the Rosia Montana Gold Corporation Mining Project

At the end of the communist era, which was characterised as a closed social experiment, Romania found itself in the middle of a globalization process. Its industrial capacities have been considerably reduced through a poor and spendthrift management. There was a mass exodus of the labour force abroad and the educational background for the remaining part was no longer in agreement with the labour market. On these grounds, the vectors of globalization, in the form of foreign investments, entered Romania effortlessly. There even were local communities where the arrival of foreign investors was expected like a second coming of Christ. This is the context in which a Canadian company set forth the mining project Rosia Montana Gold Corporation. The implementation of the project should have started in 2005. Nevertheless, the project has not been effectively launched yet. This situation is based on what we call Romanian glocalization, namely a specific confrontation between global and local on Romanian land

Romanian glocalization : Case study on the Rosia Montana Gold Corporation Mining Project

At the end of the communist era, which was characterised as a closed social experiment, Romania found itself in the middle of a globalization process. Its industrial capacities have been considerably reduced through a poor and spendthrift management. There was a mass exodus of the labour force abroad and the educational background for the remaining part was no longer in agreement with the labour market. On these grounds, the vectors of globalization, in the form of foreign investments, entered Romania effortlessly. There even were local communities where the arrival of foreign investors was expected like a second coming of Christ. This is the context in which a Canadian company set forth the mining project Rosia Montana Gold Corporation. The implementation of the project should have started in 2005. Nevertheless, the project has not been effectively launched yet. This situation is based on what we call Romanian glocalization, namely a specific confrontation between global and local on Romanian land

Romanian glocalization : Case study on the Rosia Montana Gold Corporation Mining Project

At the end of the communist era, which was characterised as a closed social experiment, Romania found itself in the middle of a globalization process. Its industrial capacities have been considerably reduced through a poor and spendthrift management. There was a mass exodus of the labour force abroad and the educational background for the remaining part was no longer in agreement with the labour market. On these grounds, the vectors of globalization, in the form of foreign investments, entered Romania effortlessly. There even were local communities where the arrival of foreign investors was expected like a second coming of Christ. This is the context in which a Canadian company set forth the mining project Rosia Montana Gold Corporation. The implementation of the project should have started in 2005. Nevertheless, the project has not been effectively launched yet. This situation is based on what we call Romanian glocalization, namely a specific confrontation between global and local on Romanian land

PanXML - a tool to create XML files for DOI registration of publications in the catalog DataCite of the German National Library of Science and Technology

The software PanXML is a tool to create XML files needed for DOI registration at the German National Library of Science and Technology (TIB). PanXML is distributed as freeware for the operating systems Microsoft Windows, Apple OS X and Linux. An XML file created by PanXML is based on the XSD file article-doi_v3.2.xsd. Further schemas may be added on request.

Patrimonio Histórico Minero-Metalúrgico, Patrimonio Cultural/ Mining-Metallurgical Historical Heritage, Cultural Heritage

El panel se divide en tres secciones : Minería histórica , Patrimonio Minero y Museos.

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.

On loader productivity, rock strength and explosive energy in metal mining

Twenty production blasts in two open pit mines were monitored, in rocks with medium to very high strength. Three different blasting agents (ANFO, watergel and emulsion blend) were used, with powder factors ranging between 0.88 and 1.45 kg/m3. Excavators were front loaders and rope shovels. Mechanical properties of the rock, blasting characteristics and mucking rates were carefully measured. A model for the calculation of the productivity of excavators is developed thereof, in which the production rate results as a product of an ideal, maximum, productivity rate times an operating efficiency. The maximum rate is a function of the dipper capacity and the efficiency is a function of rock density, strength, and explosive energy concentration in the rock. The model is statistically significant and explains up to 92 % of the variance of the production rate measurements.