Os programas de computador têm apoiado o estudo de sistemas biomédicos em que um volume considerável de dados são empregados. Na biomecânica, a análise das influências entre as articulações pode melhorar o conhecimento das lesões relacionadas à corrida associadas ao uso excessivo durante a atividade de corrida. Compreender os padrões de interação entre diferentes articulações anatômicas, durante o movimento, pode contribuir para o aprimoramento de programas de treinamento, reabilitação e prevenção a lesões. Neste trabalho, um software personalizado foi desenvolvido para implementar a Coerência Parcial Direcionada (PDC), uma abordagem no domínio da freqüência da Causalidade de Granger (GC), adequado às especificidades da fisioterapia. Com entradas independentes e padronizadas, modularização e parametrização, as rotinas investigaram a direção de interação entre diferentes canais, registrando e salvando arquivos intermediários. Separados nos três planos anatômicos, sagital, frontal e transverso, foram utilizados dados cinemáticos para analisar as interações entre tornozelo, joelho, quadril, pelve e tronco durante a corrida. Três modificações de técnica de corrida foram abordadas: com aterrissagem iniciada com o antepé, com aumento de 10% na taxa de passo e com aumento de flexão de tronco, além da habitual. As análises foram realizadas para o ciclo completo (apoio e balanço) e com separação da fase de apoio, e revelaram que essas duas estratégias de processamento são complementares. Comparando as influências proximal e distal, os procedimentos sugeriram uma predominância das interações proximal a distal, mostrando uma origem central de movimentos. Dessa forma, destaca-se a relevância em controlar e fortalecer tronco e quadril para a minimização de lesões. Considerando os resultados e a oportunidade de configuração, o software pode ser empregado para estudar outras articulações e aplicações, bem como evoluir para um sistema automatizado de apoio à decisão. / Computer programs have supported the study of biomedical systems in which a considerable amount of data is employed. In biomechanics, analysis of influences between joints can improve the knowledge of the Running-Related-Injuries (RRI) associated to overuse during running activity. Understanding the patterns of interaction among anatomical joints during movement can contribute to the improvement of training, rehabilitation and injury prevention programs. In this work, a customized software was developed to implement Partial Directed Coherence (PDC), an approach in the frequency domain of Granger Causality (GC), adapted to the physical therapy specificities. With independent and standardized inputs, modularization and parameterization, the routines investigated the interaction direction between different channels, logging and saving intermediate files. Separated in the three anatomical planes, sagittal, frontal and transverse, kinematic data were employed to analyze the interactions between ankle, knee, hip, pelvis and trunk during running. Three running technique modifications were addressed: forefoot strike landing pattern, increasing 10% of the step rate and increasing trunk flexion, in addition to usual running. The analyzes were performed for the complete cycle (stance and swing) and with separation of the stance phase, and revealed that these two processing strategies are complementary. Comparing proximal and distal influences, procedures suggested a predominance of proximal to distal interactions, showing a central origin of movements. In this way, the importance of controlling and strengthening trunk and hip to minimize injuries is highlighted. Considering the results and the processing configuration opportunity, the software can be employed to study other joints and applications, as well as evolve to an automated decision support system.

Bakgrund och Problem: Aktiemarknaden påverkas både av inhemska och utländska faktorer. Därför är det av intresse att se vilka makroekonomiska variabler som påverkar den svenska aktiemarknaden. Anledningen till att Sverige har valts som den geografiska punkten är att det är av intresse att se hur ett litet land som Sverige, som har en öppen ekonomi påverkas av de utvalda makroekonomiska variablerna. Syfte: Syftet med uppsatsen är att med hjälp av information samt analys, studera hur de olika makroekonomiska variablerna påverkar den inhemska aktiemarknaden. Olika faktorer som påverkar aktiemarknaden kommer att lyftas fram för att i sin tur även se till de olika branscherna. Metod: Då data enbart består av hämtning av tidigare information fokuseras det enbart på sekundärdata i form av historiska siffror samt historiska undersökningar. De statistiska tester som tillämpas är Granger Causality test, Johansens Cointegration test, Impulse Response Function test, ADF test, KPSS test, Mulitpel regression. Slutsats: Med de resultat som presenterades i denna studie, skulle vi nog inte kunna säga att vi har ett svar över vilka aktier en investerare ska införskaffa. Dock skulle vi kunna poängtera att den potentiella investeraren bör ha dessa variabler i beaktning vid beslut. Genom att studera dessa variabler kan man få en känsla om vilket håll variablerna kommer att röra sig och på så sätt säga att de kan påverka aktieindexen. Att bara kolla på de makroekonomiska variabler som denna studie belyser räcker inte för att förstå hur aktieindex kommer att se ut i framtiden, men det är en bit på vägen till att förstå aktiemarknadens rörelse.

Functional Magnetic Resonance Imaging (fMRI) is one of the best techniques for neuroimaging and has revolutionized the way to understand the brain functions. It measures the changes in the blood oxygen level-dependent (BOLD) signal which is related to the neuronal activity. Complexity of the data, presence of different types of noises and the massive amount of data makes the fMRI data analysis a challenging one. It demands efficient signal processing and statistical analysis methods.  The inference of the analysis is used by the physicians, neurologists and researchers for better understanding of the brain functions.      The purpose of this study is to design a toolbox for fMRI data analysis. It includes methods to detect the brain activity maps, estimation of the hemodynamic response (HDR) and the connectivity of the brain structures. This toolbox provides methods for detection of activated brain regions measured with Bayesian estimator. Results are compared with the conventional methods such as t-test, ordinary least squares (OLS) and weighted least squares (WLS). Brain activation and HDR are estimated with linear adaptive model and nonlinear method based on radial basis function (RBF) neural network. Nonlinear autoregressive with exogenous inputs (NARX) neural network is developed to model the dynamics of the fMRI data.  This toolbox also provides methods to brain connectivity such as functional connectivity and effective connectivity.  These methods are examined on simulated and real fMRI datasets.

Equity risk premium is a financial variable that is surrounded by mystery. Starting from the almost 30 year old equity premium puzzle caused by considerations that equity premium values which are observable in past data imply an implausibly high risk aversion to more recent statements that equity premium does not exist anymore. The purpose of this paper is to find out more about the traits and characteristics of equity risk premium, its current status and interactions of its values across international markets by conducting data analysis on mature equity markets using optimal methods as suggested in academic literature. This paper attempts to clear some of the confusion regarding equity premiums by analyzing equity excess returns in the mature equity markets of France, Germany, Sweden, United Kingdom and USA from 1970 to 2012. It is concluded that equity premium follows a mean reverting process however in short-term and mid-term its values can be volatile and in March 2000 there might have been a structural break. The obtained current equity premium values are significantly higher than zero. At the same time they are lower than popularly used values that are based on longer periods of past data. The paper also finds out that equity premiums in different countries are highly correlated not only due to shared global influence but also due to some direct causality relationships between them, most of which are positive. A panel data analysis is conducted as well to test the explanatory power of some macroeconomic and financial variables on the equity risk premium values and it is concluded that risk-free rate and unemployment rate have some explanatory power for equity risk premium values. This paper manages to clear a part of the mystery that surrounds the equity risk premium.

This study presents our attempt to examine the linkages and to investigate the linkage of stock price indexes among Taiwan, China and its major trading countries. Our empirical analysis employs daily data on stock price indexes over the period of January 2, 2000 to May 10, 2010. The total number of observations is about 2500. This study employ a sequence of time-series methodologies, including unit root test, cointegration test, vector error correction model, Granger causality test, Criterion, autocorrelation test, heteroscedasticity test, GARCH and Bi-GARCH. The findings of this study as follows. First, after first difference, every stock price indexes series all became stationary. Second, we found there has no long-run interrelationship among these stock markets. Third, we found that Taiwan¡¦s stock market exits leading role to China¡¦s stock market, but other countries¡¦ stock market lead Taiwan¡¦s stock market. For China, the stock market of United States, Japan, Taiwan and Hong Kong has a leading role to China¡¦s stock market. Only the rela-tionship between South Korea and China¡¦s stock market is independent. Forth, the result of autocorrelation test and ARCH test indicates that the influence of stock price indexes of major trading countries to Taiwan and China¡¦s stock price index has changed over time. Finally, the result of study indicates that every stock market can forecast its future trend by using its past stock data and investor can use the past stock data of stock market of major trading countries to forecast Taiwan and China¡¦s stock market.

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This study investigates the validity of the twin deficits hypothesis for the Turkish quarterly data over the 1988:1-2005:2 periods. To this end, we consider a VAR variable space containing budget deficits, current account deficits, real output, real interest rates and real exchange rates and employ cointegration, equilibrium/error correction mechanism techniques along with Granger-non-causality tests and impulse response analyses. The empirical results from decompositions of the budget and current account deficits into their cyclical and structural components suggest that both CAD and BD are counter-cyclical. The twin deficit hypothesis, consistent with the conventional Mundell-Flemming framework, postulates that current account and budget deficits move together in the long run and the causality runs from the former to the latter. The results from Engle-Granger and Johansen cointegration procedures support either the twin divergence or the Ricardian equivalence postulations but not the twin deficits hypothesis. Current account deficits and budget deficits are also found to be jointly endogenous. The short-run impacts of budget deficits on current account deficits are found to be mainly through the real exchange rate and real interest rate channels.

This study aims to investigate the direction of the relationship between financial deepening and economic growth after the completion of financial liberalization in Turkey. In order to do this, an unbalanced panel data set of 49 OECD and emerging countries for 1953-2005 period is examined with Granger causality and panel data estimation techniques. In the light of panel data analysis results, quarterly Turkish time series data for 1987-2006 period is examined by using Granger causality, cointegration and Vector Error Correction Model (VECM) procedures. Although the unbalanced panel data analysis reveals a relationship that is from financial deepening to economic growth, country specific Granger causality analysis employed with the panel data gives the opposite relationship for Turkey. Moreover, it is observed that quarterly time series data analysis mainly gives a relationship that is from economic growth to financial deepening.

This study is concerned with the lead-lag relationship between Turkish spot equity and derivatives markets. In the study, the spot equity market is represented by the ISE-30 Index. In order to compare the structure of the two markets, the futures contract written on the ISE-30 Index, namely TURKDEX-ISE 30, is chosen to represent the derivatives market. The analysis is performed over the sample period beginning February 4, 2005 and ending on December 10, 2010 which actually covers the entire time span from the establishment of the TURKDEX market until the end of last year. This sample period is examined on the basis of 5-minute intervals during the trading day, enabling a more detailed and accurate evaluation of the lead-lag power of the markets. The main methods applied to examine the structure of information flow between the markets are co-integration and causality analyses. Different approaches of these basic methods are employed as well in order to provide robust results. An additional robustness check is provided through examining the relationship between the markets by using both raw and filtered prices. ARMA filtering is performed on the prices and these findings are compared to those obtained by raw prices in order to avoid the problem of infrequent trading. Outcomes of both raw and filtered price analyses reveal that in 2006, 2007 and 2009 the relationship between the markets is bi-directional, whereas in 2008 and 2010, futures market strictly leads the spot market. Filtered and raw analyses do not have a definitive conclusion regarding the lead-lag relationship in 2005. For this year, while the raw data support a bi-directional relationship, ARMA filtering indicates that the spot market leads the derivatives market.

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