Akcijų rinkos yra viena svarbiausių ekonomikos sudedamųjų dalių, be jos nebūtų įmanoma įsivaizduoti nei vienos išsivysčiusios pasaulio šalies. Bendrą akcijų rinkos vertę galima laikyti, pasaulio ar konkrečios šalies, regiono ekonominiu įvertinimu. Ji pastoviai yra veikiama įvairiausių veiksnių, tokių kaip infliacija, nedarbo lygis, vartojimo lygis, palūkanų normos, fiskalinės ir monetarinės politikos, bei naftos kainų. Šis veiksnys, kaip sudedamasis akcijų rinkos vienetas yra nagrinėjamas šiame darbe. Pasak Basher ir Sadorsky (2006) naftos kainos yra modernios ekonomikos kraujas. Nors nėra lengva prognozuoti kokia bus naftos paklausa ateityje, tačiau yra aišku kad naftos paklausa yra labai stipriai koreliuota su industriniu šalies išsivystymu. Ekonomikai stiprėjant energijos paklausa (ypatingai naftos) taip pat kyla. Labai svarbu išsiaiškinti, kas šiuos kainos pokyčius lemia, ar tai ilgalaikis reiškinys bei kokius pokyčius tai gali iššaukti ateityje. Tuo pačiu labai svarbu suprasti kokią įtaką ekonomikai turi naftos kaina. Tam kad tinkamai suprasti šį poveikį reikia ištirti ar yra ryšys tarp žaliavinės naftos ir vertybinių popierių. Šiam ryšiui egzistuojant, būtina nustatyti koks jis yra. Šiame darbe nagrinėjama kaip naftos kainos įtakoja akcijų rinkas. Taip pat tiriama kokius investicinius sprendimus galima priimti atsižvelgiant į naftos kainą, ir jos pokyčius. Tyrimo objektas – Naftos kainos įtaka akcijų rinkai. Šio darbo tikslas – Nustatyti kaip naftos kainos įtakoja... [toliau žr. visą tekstą] / Stock market is one of the main parts of economy, without it it is impossible to imagine any modern country. The total value of the stock market can be taken as the whole world’s or a certain country’s, region’s economical evaluation. It is always impacted with various economical factors like inflation, unemployment rate, consumption rate, interest rates, fiscal and monetary policies and oil prices. This factor, as one of the factors to stock market, is studied in this work. According to Basher and Sadorsky (2006) oil prices is a modern economies blood. Thought it is not easy to forecast what the demand of oil will be in the coming years, but it is totally clear that demand is very strongly correlated with industrial evolution. While the economy is getting stronger the demand for energy (especially oil) is rising too. It is very important to know what is causing these variations, is it a long-term phenomenon and what changes it can make in the future. It is also very important to know what impact oil price has on economy. To properly understand this we need to analyze is there a relation between oil price and stock market. If this relation exists we need to measure it. In this work we analyze how oil prices impacts the stock market. Also we analyze what investment decisions you can make, according to oil prices and it changes. Research object – oil price impact to stock market. This works goal – to measure, how oil prices affect the stock market, and to give recommendations... [to full text]

Using the dynamic conditional correlation (DCC) model due to Engle (2002), we estimate time varying correlations of quarterly real GDP growth among the G7 countries. In general, we find that rather heterogeneous patterns of international synchronization exist during US recessions. During the 2007-2009 recession, however, international co-movement increased substantially. (authors' abstract)

Problems with students’ performance in Mathematics at tertiary level are common in South Africa − as it is worldwide. Pass rates at the university of technology where the researcher is a lecturer, are only about 50%. At many universities it has become common practice to refer students who do not have a reasonable chance to succeed at university level, for additional support to try to rectify this situation. However, the question is which students need such support? Because the Grade 12 marks are often not perceived as dependable, it has become common practice at universities to re-test students by way of an entrance exam or the "National Benchmark Test"- project. The question arises whether such re-testing is necessary, since it costs time and money and practical issues make it difficult to complete timeously. Many factors have an influence on performance in Mathematics. School-level factors include articulation of the curriculum at different levels, insufficiently qualified teachers, not enough teaching time and language problems. However, these factors also affect performance in most other subjects, but it is Mathematics and other subjects based on Mathematics that are generally more problematic. Therefore this study focused on the unique properties of the subject Mathematics. The determining role of prior knowledge, the step-by-step development of mathematical thinking, and conative factors such as motivation and perseverance were explored. Based on the belief that these factors would already have been reflected sufficiently in the Grade 12 marks, the correlation between the marks for Mathematics in Grade 12 and the Mathematics marks at tertiary level was investigated to assess whether it was strong enough for the marks in Grade 12 Mathematics to be used as a reliable predictor of success or failure at university level. It was found that the correlation between the marks for Mathematics Grade 12 and Mathematics I especially, was strong (r = 0,61). The Mathematics marks for Grade 12 and those for Mathematics II produced a correlation coefficient of rs = 0,52. It also became apparent that failure in particular could be predicted fairly accurately on the basis of the Grade 12 marks for Mathematics. No student with a Grade 12 Mathematics mark below 60% succeeded in completing Mathematics I and II in the prescribed two semesters, and only about 11% successfully completed it after one repetition. The conclusion was that the reliability of the prediction based on the marks for Grade 12 Mathematics was sufficient to refer students with a mark of less than 60% to receive some form of additional support. / MEd, Learning and Teaching, North-West University, Vaal Triangle Campus, 2011

People use orientation of their faces to convey rich, inter-personal information. For example, a person will direct his face to indicate who the intended target of the conversation is. Similarly in a conversation, face orientation is a non-verbal cue to listener when to switch role and start speaking, and a nod indicates that a person has understands, or agrees with, what is being said. Further more, face pose estimation plays an important role in human-computer interaction, virtual reality applications, human behaviour analysis, pose-independent face recognition, driver s vigilance assessment, gaze estimation, etc. Robust face recognition has been a focus of research in computer vision community for more than two decades. Although substantial research has been done and numerous methods have been proposed for face recognition, there remain challenges in this field. One of these is face recognition under varying poses and that is why face pose estimation is still an important research area. In computer vision, face pose estimation is the process of inferring the face orientation from digital imagery. It requires a serious of image processing steps to transform a pixel-based representation of a human face into a high-level concept of direction. An ideal face pose estimator should be invariant to a variety of image-changing factors such as camera distortion, lighting condition, skin colour, projective geometry, facial hairs, facial expressions, presence of accessories like glasses and hats, etc. Face pose estimation has been a focus of research for about two decades and numerous research contributions have been presented in this field. Face pose estimation techniques in literature have still some shortcomings and limitations in terms of accuracy, applicability to monocular images, being autonomous, identity and lighting variations, image resolution variations, range of face motion, computational expense, presence of facial hairs, presence of accessories like glasses and hats, etc. These shortcomings of existing face pose estimation techniques motivated the research work presented in this thesis. The main focus of this research is to design and develop novel face pose estimation algorithms that improve automatic face pose estimation in terms of processing time, computational expense, and invariance to different conditions.

Analysis of functional connectivity of simultaneously recorded multiple spike trains is one of the major issues in the neuroscience. The progress of the statistical methods to the analysis of functional connectivity of multiple spike trains is relatively slow. In this thesis two statistical techniques are presented to the analysis of functional connectivity of multiple spike trains. The first method is known as the modified correlation grid (MCG). This method is based on the calculation of cross-correlation function of all possible pair-wise spike trains. The second technique is known as the Cox method. This method is based on the modulated renewal process (MRP). The original paper on the application of the Cox method (Borisyuk et al., 1985) to neuroscience data was used to analyse only pairs and triplets of spike trains. This method is further developed in this thesis to support simultaneously recorded of any possible set of multiple spike trains. A probabilistic model is developed to test the Cox method. This probabilistic model is based on the MRP. Due to the common probabilistic basis of the probabilistic model and the Cox method, the probabilistic model is a convenient technique to test the Cox method. A new technique based on a pair-wise analysis of Cox method known as the Cox metric is presented to find the groups of coupled spike trains. Another new technique known as motif analysis is introduced which is useful in identifying interconnections among the spike trains. This technique is based on the triplet-wise analysis of the Cox method. All these methods are applied to several sets of spike trains generated by the Enhanced Leaky and Integrate Fire (ELIF) model. The results suggest that these methods are successful for analysing functional connectivity of simultaneously recorded multiple spike trains. These methods are also applied to an experimental data recorded from cat’s visual cortex. The connection matrix derived from the experimental data by the Cox method is further applied to the graph theoretical methods.

The application of fracture mechanics to engineering design has provided significant advances in understanding of the causes and mechanisms of failure and crack growth. Despite this, there are still some aspects that remain incompletely understood, such as the crack closure/crack shielding effect. The presence of crack closure/shielding acts to reduce . The mechanisms of crack closure/shielding are complicated, and have not been fully understood. This work focuses on the plasticity-induced crack tip shielding mechanism and presents a novel approach to characterise the elastic stress fields under the influence of the plastic enclave surrounding the crack tip. The model is successfully applied to determine the four stress parameters experimentally using full-field photoelastic stress analysis on polycarbonate CT specimens, following studies of the effect of the crack tip position and the valid data collection zone giving the best fit between the model predictions and the experimental data. The predicted values from the model demonstrate good data repeatability, and exhibit sensible trends as a function of crack length and load ratio that are interpretable in terms of physically meaningful changes to the plastic enclave. In addition, the model is proven to describe the stress field around a crack more accurately than classic Williams‟ stress solution. The model is also extended to AL 2024-T3 specimens using a full-field displacement measurement technique, digital image correlation. Using the Sobel edge detection method to identify the crack tip from the displacement fields with a rectangular shaped data collection zone employed in the current study, reasonable trends were again demonstrated in the experimental results as a function of crack length.

La présente thèse s'est inscrite dans une perspective d'améliorer les outils de mesure du risque de marché en proposant des solutions capables de reproduire certaines caractéristiques empiriques d'évolution des marchés financiers. A travers une étude empirique sur des données réelles, nous montrons que la réalité des marchés financiers possède certaines caractéristiques empiriques connues et résumées sous le nom "faits stylisés", qui rendent les mesures usuelles du risque de marché incapables de reproduire ces caractéristiques. Nous proposons des nouvelles méthodes de mesure de la Value-at-Risk (VaR), en fonction de la volatilité passée et des corrélations existant entre les actifs composant un portefeuille, dans le cadre de deux grandes approches de mesure du risque : une approche de mesure du risque global (ou risque univarié) et une approche de mesure du risque multiple (ou risque multivarié), tout en testant leur qualité prédictive au moyen des procédures de backtesting. Les résultats obtenus montrent une grande capacité des différentes mesures utilisées à capturer les faits stylisés caractérisant l'évolution des marchés financiers étudiés avec une nette surperformance des méthodes de mesure de la VaR estimées dans le cadre du risque multivarié par rapport à celles du risque univarié. / This thesis has object to improve the methods for estimating market risk by offering solutions capable to replicate some empirical properties of asset returns. Through an empirical study on real data, we show that the reality of financial markets has some empirical characteristics known and summarized as "stylized facts" that render the conventional market risk measurement unable to reproduce. We propose a Value-at-Risk (VaR) measures, based on modeling portfolio volatility and correlations between assets classes, using two risk measurement approaches: an univariate risk measurement approach and multivariate risk measurement approach, and testing their quality predictive using backtesting procedures. The results obtained show a great ability of different used risk measurement to capture the stylized facts characterizing financial markets, with a clear outperformance of the multivariate VaR measures than the univariate VaR measures.

In this work we present the first implementation of the incremental scheme for coupled cluster linear-response frequency-dependent dipole polarizabilities. The implementation is fully automated and makes use of the domain-specific basis set approach. The accuracy of the approach is determined on the basis of a test suite of 47 molecules and small clusters. The local approximation in the coupled cluster singles and doubles polarizability exhibits a mean error of 0.02% and a standard deviation of 0.32% when using a third-order incremental expansion. With the proposed approach, it is possible to compute polarizabilities with larger basis sets compared to the canonical implementation and thus it is possible to obtain higher total accuracy. The incremental scheme yields the smallest errors for weakly-bound and quasi-linear systems, while two- and three-dimensional (cage-like) structures exhibit somewhat larger errors as compared to the full test set. / Dieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Gene set enrichment analysis aims to discover sets of genes, such as biological pathways or protein complexes, which may show moderate but coordinated differentiation across experimental conditions. The existing gene set enrichment approaches utilize single gene statistic as a measure of differentiation for individual genes. These approaches do not utilize any inter-gene correlations, but it has been known that genes in a pathway often interact with each other. Motivated by the need for taking gene dependence into account, we propose a novel gene set enrichment algorithm, where the gene-gene correlation is addressed via a gene-pair representation strategy. Relying on an appropriately defined gene pair statistic, the gene set statistic is formulated using a competitive null hypothesis. Extensive simulation studies show that our proposed approach can correctly control the type I error (false positive rate), and retain good statistical power for detecting true differential expression. The new method is also applied to analyze several gene expression datasets. / October 2016

The objective of this study was to investigate the spatial relationship between the most likely distribution of saturated hydraulic conductivity (K-s) and the observed pressure head (P) distribution within a hillslope. The cross-correlation analysis method was used to investigate the effects of the variance of lnK(s), spatial structure anisotropy of lnK(s), and vertical infiltration flux (q) on P at some selected locations within the hillslope. The cross-correlation analysis shows that, in the unsaturated region with a uniform flux boundary, the dominant correlation between P and Ks is negative and mainly occurs around the observation location of P. A relatively high P value is located in a relatively low Ks zone, while a relatively low P value is located in a relatively high Ks zone. Generally speaking, P is positively correlated with q/Ks at the same location in the unsaturated region. In the saturated region, the spatial distribution of K-s can significantly affect the position and shape of the phreatic surface. We therefore conclude that heterogeneity can cause some parts of the hillslope to be sensitive to external hydraulic stimuli (e.g., rainfall and reservoir level change), and other parts of the hillslope to be insensitive. This is crucial to explaining why slopes with similar geometries would show different responses to the same hydraulic stimuli, which is significant to hillslope stability analysis. (C) 2016 Hohai University. Production and hosting by Elsevier B.V.