20 resultados para Efficient markets

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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[ES] Cada vez es mayor el número de empresas que optan por acudir a mercados financieros exteriores, tanto al objeto de obtener financiación en mejores condiciones, como para realizar inversiones más atractivas que las disponibles dentro de las fronteras nacionales. La decisión de internacionalizar el área financiera de la empresa puede ser el resultado de una estrategia específica orientada al aprovechamiento de las oportunidades que ofrece el proceso de globalización financiera, que se está desarrollando de forma vertiginosa los últimos años.

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This paper models the mean and volatility spillovers of prices within the integrated Iberian and the interconnected Spanish and French electricity markets. Using the constant (CCC) and dynamic conditional correlation (DCC) bivariate models with three different specifications of the univariate variance processes, we study the extent to which increasing interconnection and harmonization in regulation have favoured price convergence. The data consist of daily prices calculated as the arithmetic mean of the hourly prices over a span from July 1st 2007 until February 29th 2012. The DCC model in which the variances of the univariate processes are specified with a VARMA(1,1) fits the data best for the integrated MIBEL whereas a CCC model with a GARCH(1,1) specification for the univariate variance processes is selected to model the price series in Spain and France. Results show that there are significant mean and volatility spillovers in the MIBEL, indicating strong interdependence between the two markets, while there is a weaker evidence of integration between the Spanish and French markets. We provide new evidence that the EU target of achieving a single electricity market largely depends on increasing trade between countries and homogeneous rules of market functioning.

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[En]The present study aimed at investigating the existence of long memory properties in ten developed stock markets across the globe. When return series exhibit long memory, the series realizations are not independent over time and past returns can help predict future returns, thus violating the market efficiency hypothesis. It poses a serious challenge to the supporters of random walk behavior of the stock returns indicating a potentially predictable component in the series dynamics. We computed Hurst-Mandelbrot’s Classical R/S statistic, Lo’s statistic and semi parametric GPH statistic using spectral regression. The findings suggest existence of long memory in volatility and random walk for logarithmic return series in general for all the selected stock market indices. Findings are in line with the stylized facts of financial time series.

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Boron nitride is a promising material for nanotechnology applications due to its two-dimensional graphene-like, insulating, and highly-resistant structure. Recently it has received a lot of attention as a substrate to grow and isolate graphene as well as for its intrinsic UV lasing response. Similar to carbon, one-dimensional boron nitride nanotubes (BNNTs) have been theoretically predicted and later synthesised. Here we use first principles simulations to unambiguously demonstrate that i) BN nanotubes inherit the highly efficient UV luminescence of hexagonal BN; ii) the application of an external perpendicular field closes the electronic gap keeping the UV lasing with lower yield; iii) defects in BNNTS are responsible for tunable light emission from the UV to the visible controlled by a transverse electric field (TEF). Our present findings pave the road towards optoelectronic applications of BN-nanotube-based devices that are simple to implement because they do not require any special doping or complex growth

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The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.

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[EN] The purpose of this review article is to illustrate synthetic aspects of functionalized phosphorus derivatives containing an oximo moiety at the beta-position. First section will be focused on the synthesis of phosphine oxides, phosphonates or phosphonium salts containing an oxime group. The synthesis of these derivatives comprises the carbon–phosphorus single bond construction by reaction of haloximes with phosphorus derivatives, nucleophilic addition of phosphorus reagents to carbonyl compounds, or nucleophilic addition of phosphorus reagents to nitro olefins. This section will also concentrate on the most practical routes for the synthesis of the target compounds, through carbon–nitrogen double bond formation, which are as follows: condensation processes of carbonyl compounds and hydroxylamine derivatives or addition of hydroxylamines to allenes or alkynes. The preparative use of beta-oximo phosphorus derivatives as synthetic intermediates will be discussed in a second section, comprising olefination reaction, oxidation of oximes to nitrile oxides by reaction at the C-N double bond of the oxime moiety, oxidation of these substrates to nitrosoalkenes, reduction to the corresponding hydroxylamines and some reactions at the hydroxyl group of the hydroxyimino moiety.

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36 p.

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This project analyses the influence of the futures market on middle and low income countries. In it, I attempt to show that investments made by large investment funds in this market, as well as by certain pension plans, bring major consequences whose effects are more evident in less developed countries. The cornerstones of the work are as follows; to attempt to see the existing relationship between the commodity futures market and its underlying assets; analysing products such as wheat, rice and corn in-depth, because these are the most basic foodstuffs at a global level; to determine how an increase in trading in these markets can affect the lives of people in the poorest countries; to analyse investor concern regarding the consequences that their investments may have. Throughout the project we will see how large speculators use production forecasting models to determine the shortage of a commodity in order to take a position in the futures market to profit from it. In addition we will see how an increase in trading in this market causes an increase in the price of the underlying asset in the spot market. As for investor concern, I can say it is negligible, but the idea of running pension plans or investment funds that follow some social criteria has been welcomed by those interviewed, which makes me think that different legislation is possible. This legislation will only come into existence if it is demanded by the people. A fact that now becomes complicated because without a minimum financial basis, they cannot even know how the large investment funds trade with hunger in the world. The day when most people understand how large speculators profit from famine will be the day to put pressure on governments to begin to put limits on speculation. This makes financial awareness necessary in order to achieve a curb in excessive speculation.

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[EN] In the modern era firms should look for a sustainable and profitable business model. They operate in highly volatile and competitive markets. Innovation is a key element that allows firms to survive in these complex environments. Accordingly, some companies are developing human resource models that align to the actual competitive context. For instance, they establish democratic systems, flexible work practices, they focus on responsibility and initiative and increase the self-control of team members. In this framework, firms tend to use resources such as creativity, capacity for innovation or development of human talent. Therefore, innovative teams are able to adapt and react to turbulent, complex and dynamic environments, which allow them to handle in a more efficient way several subtasks. This fact gives rise to a higher effectiveness in the activities of firms. This paper analyze the characteristics and performance of multifunctional teams, virtual teams, open-innovation teams and self-managing teams. It also study the case of Semco, a company that is characterized by its innovative practices in human resources management and focus on responsibility and initiative and increase the self-control of team members.

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Enzyme-catalyzed production of biodiesel is the object of extensive research due to the global shortage of fossil fuels and increased environmental concerns. Herein we report the preparation and main characteristics of a novel biocatalyst consisting of Cross-Linked Enzyme Aggregates (CLEAs) of Candida antarctica lipase B (CALB) which are covalently bound to magnetic nanoparticles, and tackle its use for the synthesis of biodiesel from non-edible vegetable and waste frying oils. For this purpose, insolubilized CALB was covalently cross-linked to magnetic nanoparticles of magnetite which the surface was functionalized with –NH2 groups. The resulting biocatalyst combines the relevant catalytic properties of CLEAs (as great stability and feasibility for their reutilization) and the magnetic character, and thus the final product (mCLEAs) are superparamagnetic particles of a robust catalyst which is more stable than the free enzyme, easily recoverable from the reaction medium and reusable for new catalytic cycles. We have studied the main properties of this biocatalyst and we have assessed its utility to catalyze transesterification reactions to obtain biodiesel from non-edible vegetable oils including unrefined soybean, jatropha and cameline, as well as waste frying oil. Using 1% mCLEAs (w/w of oil) conversions near 80% were routinely obtained at 30°C after 24 h of reaction, this value rising to 92% after 72 h. Moreover, the magnetic biocatalyst can be easily recovered from the reaction mixture and reused for at least ten consecutive cycles of 24 h without apparent loss of activity. The obtained results suggest that mCLEAs prepared from CALB can become a powerful biocatalyst for application at industrial scale with better performance than those currently available.

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Neurons obtained directly from human somatic cells hold great promise for disease modeling and drug screening. Available protocols rely on overexpression of transcription factors using integrative vectors and are often slow, complex, and inefficient. We report a fast and efficient approach for generating induced neural cells (iNCs) directly from human hematopoietic cells using Sendai virus. Upon SOX2 and c-MYC expression, CD133-positive cord blood cells rapidly adopt a neuroepithelial morphology and exhibit high expansion capacity. Under defined neurogenic culture conditions, they express mature neuronal markers and fire spontaneous action potentials that can be modulated with neurotransmitters. SOX2 and c-MYC are also sufficient to convert peripheral blood mononuclear cells into iNCs. However, the conversion process is less efficient and resulting iNCs have limited expansion capacity and electrophysiological activity upon differentiation. Our study demonstrates rapid and efficient generation of iNCs from hematopoietic cells while underscoring the impact of target cells on conversion efficiency.