Dissertations / Theses on the topic 'SAPPhIRE Model of Causality'
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1
Johansson, Magnus, and Johan Kingstedt. "Methods for Residual Generation Using Mixed Causality in Model Based Diagnosis." Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-12062.
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Several different air pollutions are produced during combustion in a diesel engine, for example nitric oxides, NOx, which can be harmful for humans. This has led to stricter emission legislations for heavy duty trucks. The law requires both lower emissions and an On-Board Diagnosis system for all manufactured heavy duty trucks. The OBD system supervises the engine in order to keep the emissions below legislation demands. The OBD system shall detect malfunctions which may lead to increased emissions. To design the OBD system an automatic model based diagnosis approach has been developed at Scania CV AB where residual generators are generated from an engine model.
The main objective of this thesis is to improve the existing methods at Scania CV AB to extract residual generators from a model in order to generate more residual generators. The focus lies on the methods to find possible residual generators given an overdetermined subsystem. This includes methods to estimate derivatives of noisy signals.
A method to use both integral and derivative causality has been developed, called mixed causality. With this method it has been shown that more residual generators can be found when designing a model based diagnosis system, which improves the fault isolation. To use mixed causality, derivatives are estimated with smoothing spline approximation.
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Guo, Yuanxiang. "Chinese wheat price analysis - with application of cointegration and Granger causality test." Thesis, Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/52978.
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Traditional demonstration of price fluctuation in the wheat market, by the theory of supply and demand is not comprehensive enough. With limited understanding of macroeconomic effects on the wheat market, accurate prediction of wheat price is impossible. Given the Chinese self—sustainable food policy, grain imports is a sensitive topic which may incur fierce argument. In this paper, however, I emphasize effect of exchange rate on nominal wheat price. By application of the cointegration theory, CPI shows slight negative correlation with nominal wheat price, yet GDP and population move in the same direction as the wheat price. The cointegration study of exchange rate implies, with appreciating Chinese RMB, domestic buyers incline to purchase wheat from the cheaper foreign market. According to the Granger causality test, the whole package of variables suggests significant causal relation with the wheat price.
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Vang, Jee. "Using a model of human cognition of causality to orient arcs in structural learning of Bayesian networks." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3386.
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Thesis (Ph.D.)--George Mason University, 2008.Vita: p. 249. Thesis director: Farrokh Alemi. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computational Sciences and Informatics. Title from PDF t.p. (viewed Mar. 16, 2009). Includes bibliographical references (p. 238-248). Also issued in print.
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Hubálek, Ondřej. "Grafické modely ve statistice a ekonometrii." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-165317.
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Graphical models in statistics and econometrics provide capability to describe causal relations using causal graph in classical regression analysis and others econometric tools. Goal of this thesis is description of causal modelling of time series with help of structural models of vector autoregression. There is description of procedure of building structural VAR model, principle of graphical models and building model for causal dependence analysis. For purpose of comparison there are used data from both USA and Czech Republic and comparison of similar models for both countries is presented. Best models are then selected, to show causal relations between macroeconomic variables. For purpose of analysis, impulse-response functions are used to show impact of demand shock on GDP and other macro indicators.
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Omran, Hayan. "Examining the relationship between trading volume, market return volatility and U.S. aggregate mutual fund flow." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12848.
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This thesis consists of three studies which cover topics in the trading volume-market return volatility linkage, stock market return-aggregate mutual fund flow relationship as well as market return volatility-aggregate mutual fund flow interaction. Chapter 2 investigates the issue of volume-volatility linkage in the US market for the period 1990-2012 (S&P 500) and 1992-2012 (Dow Jones). We construct four sub-samples depending on three different structural points (the Asian Financial Crisis, the Dot-Com Bubble and the 2007 Financial Crisis). By employing univariate and bivariate GARCH processes, we find positive (negative) bidirectional linkages between these two aforementioned variables in various cases of the estimation, while a mixed one is observed in the remainder of these cases. Chapter 3 examines the issue of temporal ordering of the range-based stock market return (S&P 500 index) and aggregate mutual fund flow in the U.S. market for the period 1998-2012. We construct nine sub-samples represented by three fundamental cases of the whole data set. In addition, we take into consideration three essential indicators when splitting the whole data set, which are the 2000 Dot-Com Bubble, the 2007 Financial Crisis as well as the 2009 European Sovereign Debt Crisis. We examine the dynamics of the return-flow interaction by employing bivariate VAR model with various specifications of GARCH approach. Our principal findings display a bidirectional mixed feedback between stock market return and aggregate mutual fund flow for the majority of the sub-samples obtained. Nevertheless, we provide limited evidence of a positive bi-directional causality between return and flow. Chapter 4 investigates the dynamic relation between S&P 500 return volatility and U.S. aggregate mutual fund flow for the period spanning between 1998 and 2012. We assess the dynamics of the volatility-flow linkage by employing a bivariate VAR model with the GARCH approach which allows for long memory in the mean and the variance equations. In addition to the sub-samples obtained in chapter 3, we generate two measurements of volatility. Our baseline results indicate a variety of bidirectional mixed causalities between market return volatility and aggregate mutual fund flow in several sub-samples. In addition, we observe a negative/positive bi-directional relationship between volatility and flow in the rest of the sub-periods. Summarizing, a range of our findings are in line with the empirical underpinnings that most likely predict a significant linkage between the aforementioned variables. Finally, most of the bidirectional effects are found to be quite robust to the dynamics of the various GARCH processes employed in this thesis.
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Kayesh, Humayun. "Deep Learning for Causal Discovery in Texts." Thesis, Griffith University, 2022. http://hdl.handle.net/10072/415822.
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Causality detection in text data is a challenging natural language processing task. This is a trivial task for human beings as they acquire vast background knowledge throughout their lifetime. For example, a human knows from their experience that heavy rain may cause flood or plane accidents may cause death. However, it is challenging to automatically detect such causal relationships in texts due to the availability of limited contextual information and the unstructured nature of texts. The task is even more challenging for social media short texts such as Tweets as often they are informal, short, and grammatically incorrect. Generating hand-crafted linguistic rules is an option but is not always effective to detect causal relationships in text because they are rigid and require grammatically correct sentences. Also, the rules are often domain-specific and not always portable to another domain. Therefore, supervised learning techniques are more appropriate in the above scenario. Traditional machine learning-based model also suffers from the high dimensional features of texts. This is why deep learning-based approaches are becoming increasingly popular for natural language processing tasks such as causality detection. However, deep learning models often require large datasets with high-quality features to perform well. Extracting deeply-learnable causal features and applying them to a carefully designed deep learning model is important. Also, preparing a large human-labeled training dataset is expensive and time-consuming. Even if a large training dataset is available, it is computationally expensive to train a deep learning model due to the complex structure of neural networks. We focus on addressing the following challenges: (i) extracting highquality causal features, (ii) designing an effective deep learning model to learn from the causal features, and (iii) reducing the dependency on large training datasets. Our main goals in this thesis are as follows: (i) we aim to study the different aspects of causality and causal discovery in text in depth. (ii) We aim to develop strategies to model causality in text, (iii) and finally, we aim to develop frameworks to design effective and efficient deep neural network structures to discover causality in texts.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Info & Comm Tech
Science, Environment, Engineering and Technology
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Karl, Velander, and Callerud Karin. "The development of the financialsystem and economic growth in Sweden : A Granger causality analysis." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-78703.
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Binase, Uviwe. "Socioeconomic determinants of life expectancy in post-apartheid South Africa." University of the Western Cape, 2018. http://hdl.handle.net/11394/6790.
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Magister Philosophiae - MPhilLife expectancy in South African has been fluctuating following the global trends that affects both developed and developing countries. In South Africa the average life expectancy from 1994 to 1996 was higher with an average of 61,3 years. As from 1997 to 1999 it declined to an average of 58,4 years. The difference in years between 1994-1996 and 1997- 1999 was 2,9 years. From 2000-2002, life expectancy continued to decline to an average of 54,6 years. Life expectancy declined in a constant proportion from 2003-2005 and 2006-2008. In 2003-2005 it slightly declined to 52 years and in 2004-2007 it declined to 42,0 years. Life expectancy escalated after the mentioned years to 54,4 years between 2009-2011 and from 2012-2013 life expectancy was 54,0 years on average. This study examined factors or variables that verify the socioeconomic determinants of life expectancy in post-apartheid South Africa. Understanding the relationship between life expectancy and the socioeconomic variables was based on three objectives. The main objective for this study was to determine the impact of socioeconomic variables and health policy efforts on life expectancy, seeking an in-depth understanding by investigating the causality relationship between life expectancy and socioeconomic variables thus later investigating the difference between male and female’s life expectancy. This study was motivated by the fluctuating life expectancy in South Africa. The fluctuation in life expectancy were thus studied in relation to socioeconomic determinants which are government health expenditure, government education expenditure, GDP per capita, total fertility rate, urban population, access to sustainable drinking water and undernourishment. The mentioned variables were used as socioeconomic determinants of life expectancy during post-apartheid South Africa.
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Strikholm, Birgit. "Essays on nonlinear time series modelling och hypothesis testing." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-535.
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There seems to be a common understanding nowadays that the economy is nonlinear. Economic theory suggests features that can not be incorporated into linear frameworks, and over the decades a solid body of empirical evidence of nonlinearities in economic time series has been gathered. This thesis consists of four essays that have to do with various forms of nonlinear statistical inference. In the first chapter the problem of determining the number regimes in a threshold autoregressive (TAR) model is considered. Typically, the number of regimes (or thresholds) is assumed unknown and has to be determined from the data. The solution provided in the chapter first uses the smooth transition autoregressive (STAR) model with a fixed and rapid transition to approximate the TAR model. The number of thresholds is then determined using sequential misspecification tests developed for the STAR model. The main characteristic of the proposed method is that only standard statistical inference is used, as opposed to non-standard inference or computation intensive bootstrap-based methods. In the second chapter a similar idea is employed and the structural break model is approximated with a smoothly time-varying autoregressive model. By making the smooth changes in parameters rapid, the model is able to closely approximate the corresponding model with breaks in the parameter structure. This approximation makes the misspecification tests developed for the STR modelling framework available and they can be used for sequentially determining the number of breaks. Again, the method is computationally simple as all tests rely on standard statistical inference. There exists literature suggesting that business cycle fluctuations affect the pattern of seasonality in macroeconomic series. A question asked in the third chapter is whether other factors such as changes in institutions or technological change may have this effect as well. The time-varying smooth transition autoregressive (TV- STAR) models that can incorporate both types of change are used to model the (possible) changes in seasonal patterns and shed light on the hypothesis that institutional and technological changes (proxied by time) may have a stronger effect on seasonal patterns than business cycle. The TV-STAR testing framework is applied to nine quarterly industrial production series from the G7 countries, Finland and Sweden. These series display strong seasonal patterns and also contain the business cycle fluctuations. The empirical results of the chapter suggest that seasonal patterns in these series have been changing over time and, furthermore, that the business cycle fluctuations do not seem to be the main cause for this change. The last chapter of the thesis considers the possibility of testing for Granger causality in bivariate nonlinear systems when the exact form of the nonlinear relationship between variables is not known. The idea is to linearize the testing problem by approximating the nonlinear system by its Taylor expansion. The expansion is linear in parameters and one gets round the difficulty caused by the unknown functional form of the relationship under investigation.Diss. Stockholm : Handelshögskolan, 2004
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Germeys, Jasper. "Supervision of the Air Loop in the Columbus Module of the International Space Station." Thesis, Linköpings universitet, Fordonssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133926.
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Failure detection and isolation (FDI) is essential for reliable operations of complex autonomous systems or other systems where continuous observation or maintenance thereof is either very costly or for any other reason not easily accessible. Beneficial for the model based FDI is that there is no need for fault data to detect and isolate a fault in contrary to design by data clustering. However, it is limited by the accuracy and complexity of the model used. As models grow more complex, or have multiple interconnections, problems with the traditional methods for FDI emerge. The main objective of this thesis is to utilise the automated methodology presented in [Svärd, 2012] to create a model based FDI system for the Columbus air loop. A small but crucial part of the life support on board the European space laboratory Columbus. The process of creating a model based FDI, from creation of the model equations, validation thereof to the design of residuals, test quantities and evaluation logic is handled in this work. Although the latter parts only briefly which leaves room for future work. This work indicate that the methodology presented is capable to create quite decent model based FDI systems even with poor sensor placement and limited information of the actual design. [] Carl Svärd. Methods for Automated Design of Fault Detection and Isolation Systems with Automotive Applications. PhD thesis, Linköping University, Vehicular Systems, The Institute of Technology, 2012
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Momoli, Tommaso. "Financialization of the commodity future markets: a SVAR model approach." Master's thesis, reponame:Repositório Institucional do FGV, 2017. http://hdl.handle.net/10362/26207.
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Submitted by Tommaso Momoli (tommaso.momoli@gmail.com) on 2017-03-29T04:51:52Z
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This is a study regarding the impact of the index investments in the Commodity Future Market. The models applied, focus on the Causal Analysis and the Impulse Response Function through an orthogonalisation of the Vector of Auto Regression (SVAR), this allow to extract lead/lag correlation between the Index and First nearby Return for different Futures Sectors and in addition response to shocks in different equation. The study is divided in three different period, to reflect before and after the Financialization and then after the introduction in the market of the new generation of commodity Indexes. The results show a different behaviors of the parameters throughout time with a particular emphasis for the most traded Commodities to lead the others.
Trata-se de um estudo sobre o impacto dos investimentos em índices no mercado futuro de commodities. Os modelos aplicados, enfocam a Análise Causal e a Função de Resposta ao Impulso através de uma ortogonalização do Vetor de Auto Regressão (SVAR), permitindo extrair a correlação lead / lag entre o Índice e o Primeiro Retorno próximo para diferentes Setores Futuros e, A choques em diferentes equações. O estudo é dividido em três períodos diferentes, para refletir antes e depois da Financialização e, em seguida, após a introdução no mercado da nova geração de índices de commodities. Os resultados mostram um comportamento diferente dos parâmetros ao longo do tempo com uma ênfase particular para os Commodities mais negociados para liderar os outros.
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Ko, Hsiu-Hsin. "Three Essays on Exchange Rates and Fundamentals." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1245264972.
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RAMAZZOTTI, DANIELE. "A Model of Selective Advantage for the Efficient Inference of Cancer Clonal Evolution." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2016. http://hdl.handle.net/10281/100453.
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Recently, there has been a resurgence of interest in rigorous and scalable algorithms for efficient inference of cancer progression using genomic patient data. The motivations are manifold: (i) rapidly growing NGS and single cell data from cancer patients, (ii) long-felt need for novel Data Science and Machine Learning algorithms well-suited for inferring models of cancer progression, and finally, (iii) a desire to understand the temporal and heterogeneous structure of tumor so as to tame its natural progression through most efficacious therapeutic intervention. This thesis presents a multi-disciplinary effort to algorithmically and efficiently model tumor progression involving successive accumulation of genetic alterations, each resulting populations manifesting themselves with a novel cancer phenotype.
The framework presented in this work along with efficient algorithms derived from it, represents a novel and versatile approach for inferring cancer progression, whose accuracy and convergence rates surpass other existing techniques. The approach derives its power from many insights from, and contributes to, several fields including algorithms in machine learning, theory of causality, and cancer biology. Furthermore, an optimal, versatile and modular pipeline to extract ensemble-level progression models from cross-sectional sequenced cancer genomes is also proposed. The pipeline combines state-of-the-art techniques for sample stratification, driver selection, identification of fitness-equivalent exclusive alterations and progression model inference.
Finally, the results are rigorously validated using synthetic data created with realistic generative models, and empirically interpreted in the context of real cancer datasets; in the later case, biologically significant conclusions revealed by the reconstructed progressions are also highlighted. Specifically, the pipeline's ability to reproduce much of the current knowledge on colorectal cancer progression, as well as to suggest novel experimentally verifiable hypotheses is also demonstrate. Lastly, it is also proved that the proposed framework can be applied, mutatis mutandis, in reconstructing the evolutionary history of cancer clones in single patients, as illustrated by an example with multiple biopsy data from clear cell renal carcinomas.
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Mello, Eduardo Morato. "In search of exchange rate predictability: a study about accuracy, consistency, and granger causality of forecasts generated by a Taylor Rule Model." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/13308.
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Este estudo investiga o poder preditivo fora da amostra, um mês à frente, de um modelo baseado na regra de Taylor para previsão de taxas de câmbio. Revisamos trabalhos relevantes que concluem que modelos macroeconômicos podem explicar a taxa de câmbio de curto prazo. Também apresentamos estudos que são céticos em relação à capacidade de variáveis macroeconômicas preverem as variações cambiais. Para contribuir com o tema, este trabalho apresenta sua própria evidência através da implementação do modelo que demonstrou o melhor resultado preditivo descrito por Molodtsova e Papell (2009), o 'symmetric Taylor rule model with heterogeneous coefficients, smoothing, and a constant'. Para isso, utilizamos uma amostra de 14 moedas em relação ao dólar norte-americano que permitiu a geração de previsões mensais fora da amostra de janeiro de 2000 até março de 2014. Assim como o critério adotado por Galimberti e Moura (2012), focamos em países que adotaram o regime de câmbio flutuante e metas de inflação, porém escolhemos moedas de países desenvolvidos e em desenvolvimento. Os resultados da nossa pesquisa corroboram o estudo de Rogoff e Stavrakeva (2008), ao constatar que a conclusão da previsibilidade da taxa de câmbio depende do teste estatístico adotado, sendo necessária a adoção de testes robustos e rigorosos para adequada avaliação do modelo. Após constatar não ser possível afirmar que o modelo implementado provém previsões mais precisas do que as de um passeio aleatório, avaliamos se, pelo menos, o modelo é capaz de gerar previsões 'racionais', ou 'consistentes'. Para isso, usamos o arcabouço teórico e instrumental definido e implementado por Cheung e Chinn (1998) e concluímos que as previsões oriundas do modelo de regra de Taylor são 'inconsistentes'. Finalmente, realizamos testes de causalidade de Granger com o intuito de verificar se os valores defasados dos retornos previstos pelo modelo estrutural explicam os valores contemporâneos observados. Apuramos que o modelo fundamental é incapaz de antecipar os retornos realizados.
This study investigates whether a Taylor rule-based model provides short-term, one-month-ahead, out-of-sample exchange-rate predictability. We review important research that concludes that macroeconomic models are able to forecast exchange rates over short horizons. We also present studies that are skeptical about the forecast predictability of exchange rates with fundamental models. In order to provide our own evidence and contribution to the discussion, we implement the model that presents the strongest results in Molodtsova and Papell’s (2009) influential paper, the 'symmetric Taylor rule model with heterogeneous coefficients, smoothing, and a constant.' We use a sample of 14 currencies vis-à-vis the US dollar to make out-of-sample monthly forecasts from January 2000 to March 2014. As with the work of Galimberti and Moura (2012), we focus on free-floating exchange rate and inflation-targeting economies, but we use a sample of both developed and developing countries. In line with Rogoff and Stavrakeva (2008), we find that the conclusion about a model’s out-of-sample exchange-rate forecast capability largely depends on the test statistics used: it is necessary to use stringent and robust test statistics to properly evaluate the model. After concluding that it is not possible to claim that the forecasts of the implemented model are more accurate than those of a random walk, we inquire as to whether the fundamental model is at least capable of providing 'rational,' or 'consistent,' predictions. To test this, we adopt the theoretical and procedural framework laid out by Cheung and Chinn (1998). We find that the implemented Taylor rule model’s forecasts do not meet the 'consistent' criteria. Finally, we implement Granger causality tests to verify whether lagged predicted returns are able to partially explain, or anticipate, the actual returns. Once again, the performance of the structural model disappoints, and we are unable to confirm that the lagged forecasted returns antedate the actual returns.
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Momoli, Tommaso. "Financialization of the commodity future markets: a SVAR model approach." reponame:Repositório Institucional do FGV, 2017. http://hdl.handle.net/10438/18105.
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Submitted by Tommaso Momoli (tommaso.momoli@gmail.com) on 2017-03-29T04:51:52Z
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This is a study regarding the impact of the index investments in the Commodity Future Market. The models applied, focus on the Causal Analysis and the Impulse Response Function through an orthogonalisation of the Vector of Auto Regression (SVAR), this allow to extract lead/lag correlation between the Index and First nearby Return for different Futures Sectors and in addition response to shocks in different equation. The study is divided in three different period, to reflect before and after the Financialization and then after the introduction in the market of the new generation of commodity Indexes. The results show a different behaviors of the parameters throughout time with a particular emphasis for the most traded Commodities to lead the others.
Trata-se de um estudo sobre o impacto dos investimentos em índices no mercado futuro de commodities. Os modelos aplicados, enfocam a Análise Causal e a Função de Resposta ao Impulso através de uma ortogonalização do Vetor de Auto Regressão (SVAR), permitindo extrair a correlação lead / lag entre o Índice e o Primeiro Retorno próximo para diferentes Setores Futuros e, A choques em diferentes equações. O estudo é dividido em três períodos diferentes, para refletir antes e depois da Financialização e, em seguida, após a introdução no mercado da nova geração de índices de commodities. Os resultados mostram um comportamento diferente dos parâmetros ao longo do tempo com uma ênfase particular para os Commodities mais negociados para liderar os outros.
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Sax, Kaijser Per. "Tobin’s Q theory and regional housing investment : Empirical analysis on Swedish data." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-226661.
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This thesis investigates the relationship between Tobin’s Q and regional housing investment in Sweden for the time period of 1998-2012. The relationship is tested through estimation of two models for time-series analysis, a vector error correction model (VECM) and an autoregressive distributed lag (ARDL) model. Depending on which model that is used, I find some evidence of positive correlation between Tobin’s Q and regional housing investment in the long run while the short run dynamics of investment does not seem to be explained by Tobin’s Q. By transforming the regional data into a panel data set and running a fixed effects model, I examine the gain in explanatory power of Tobin’s Q from using disaggregated data rather than aggregated. My findings suggest that using disaggregated data improves the explanatory power of Tobin’s Q on investment. However, the Granger Causality test indicates two-way causality between Tobin’s Q and investment, causing endogeneity problem in the estimated equations.
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Lytsenko, M., Тетяна Олександрівна Маринич, Татьяна Александровна Маринич, and Tetiana Oleksandrivna Marynych. "Econometric modeling of nonstationary processes." Thesis, Karazin National University, 2015. http://essuir.sumdu.edu.ua/handle/123456789/68631.
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Econometric research of nonstationary time series on causality, cointegration relation and adequate simulation methods was conducted. VAR and VEC models were found to be the most appropriate ways to make reliable prediction and scenario analysis of macro financial data under unstable economic conditions. These econometric techniques were approbated on the financial indicators of Ukrainian economy.
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Avena, Anna. "Analyzing brain connectivity of disorder of consciousness patients with a multi-variate, time-dependent and adaptive arma model." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20409/.
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Nell'ambito delle neuroscienze vengono effettuati sempre più studi al fine di comprendere meglio le reti cerebrali e le loro dinamiche. La comunità scientifica ha condotto numerosi studi ed esperimenti sulle normali funzioni cerebrali umane, ma solo recentemente un discreto numero di ricercatori ha rivolto la propria attenzione all'analisi di diversi disturbi cerebrali, tra cui i disturbi della coscienza (Disorders of Consciousness o DoC).
Un DoC è uno stato in cui viene meno la capacità psichica e cognitiva della persona e quest'ultima non mostra segni di veglia e/o di consapevolezza.
Questa tesi mira a sviluppare un modello che consente di analizzare la connettività neurale tra le diverse aree cerebrali e fare inferenze sullo stato dei pazienti affetti da DOC al fine di supportare e affiancare gli attuali criteri diagnostici e migliorare così il processo decisionale medico.
L'approccio utilizzato per raggiungere questo obiettivo si basa sul concetto di causalità di Granger (G-causality). Questo metodo permette l'identificazione delle interazioni causali all'interno del cervello e può essere tracciato attraverso un modello autoregressivo a media mobile (ARMA) basato sull'algoritmo delle trasformazioni di Fourier (FT).
In particolare, in questa tesi è stata implementata una peculiare normalizzazione della G-causality denominata coerenza parziale diretta (PDC).
La PDC mira a stimare la connettività tra coppie di neuroni e i risultati mostrano quanto siano forti tali connessioni, permettendo così l'identificazione di pattern e la comparazione fra i diversi stati tipici dei disturbi della coscienza.
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Svärd, Carl, and Henrik Wassén. "Development of Methods for Automatic Design of Residual Generators." Thesis, Linköping University, Department of Electrical Engineering, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7931.
Full textAbstract:
Legislation requires substantially lowered emissions and that all trucks manufactured are equipped with an On-Board Diagnosis (OBD) system. One approach for designing an OBD system is to use model based diagnosis and residual generation. At Scania CV AB, a method for automatic design of a diagnosis system from a model has been developed but there are still possibilities for improvements to get more and better residual generators. The main objective of this thesis is to analyze and improve the existing method.
A theoretic outline of two methods using different causality assumptions is presented and the differences are analyzed and discussed. Stability of residual generators is analyzed and a method for constructing stable residual generators and its consequences for the diagnosis system is presented.
Methods using integral and derivative causality are found not to be equivalent for all dynamic systems, resulting in that a diagnosis system utilizing both methods would be preferred for detectability reasons. A stable residual generator can be constructed from an unstable residual generator. The method for stabilizing a residual generator affects the fault sensitivity of the residual generator and the fault detectability properties of the diagnosis system.
Lagkrav kräver väsentligt sänkta emissionsnivåer och att alla tillverkade lastbilar är utrustade med ett system för On-Board Diagnosis (OBD). Ett sätt att konstruera ett OBD system är att använda modellbaserad diagnos och residualgenerering. På Scania CV AB har en metod för automatisk konstruktion av ett diagnossystem utifrån en modell utvecklats, men det finns utrymme för bättringar som leder till att fler och bättre residualgeneratorer konstrueras. Huvudsyftet med examensarbetet är att analysera och förbättra den existerande metoden.
En teoretisk beskrivning av två metoder som använder sig av olika kausalitet presenteras och skillnaderna analyseras och diskuteras. Stabiliteten hos residualgeneratorer analyseras och en metod för att konstruera stabila residualgeneratorer och dess konsekvenser för diagnossystemet presenteras.
Metoder som använder sig av integrerande respektive deriverande kausalitet visar sig inte vara ekvivalenta för alla dynamiska system, vilket resulterar i att ett diagnossystem som använder sig av båda kausaliteterna är att föredra i ett diagnossystem med avseende på detekterbarhet. En stabil residualgenerator kan konstrueras från en instabil residualgenerator. Metoden för att stabilisera en residualgenerator påverkar felkänsligheten hos residualgeneratorn och feldetekterbarheten hos diagnossystemet.
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Murakami, Patricia Nagami. "Causalidade Granger em medidas de risco." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-14072011-221932/.
Full textAbstract:
Esse trabalho apresenta um estudo da causalidade de Granger em Risco bivariado aplicado a séries temporais financeiras. Os eventos de risco, no caso de séries financeiras, estão relacionados com a avaliação do Valor em Risco das posições em ativos. Para isso, os modelos CaViaR, que fazem parte do grupo de modelos de Regressão Quantílica, foram utilizado para identificação desses eventos. Foram expostos os conceitos principais envolvidos da modelagem, assim como as definições necessárias para entendê-las. Através da análise da causalide de Granger em risco entre duas séries, podemos investigar se uma delas é capaz de prever a ocorrência de um valor extremo da outra. Foi realizada a análise de causalidade de Granger usual somente para como comparativo.Quantile Regression, Value at Risk, CAViaR Model, Granger Causality, Granger Causality in Risk
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Maxa, Jan. "Analýha a komparace inflace v ČR a SRN." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-124610.
Full textAbstract:
The aim of this paper is to analyse and compare inflation and its dynamics between two countries -- the Czech Republic and Germany -- applying a special kind of econometric models. The first part of this paper is dedicated to economic theory of inflation -- fundamental terms, measuring methods and its targeting. The monetary policy in the Czech Republic and Germany is also shortly introduced. Next chapter tries to describe the econometric concept which is used in this paper -- vector autoregression model (VAR model). In connection with the VAR models, Granger causality, impulse response function, cointegration and error correction model are mentioned as well. The empirical part includes application of selected models on real time series of macroeconomic indicators. Next to the interpretation of results, the forecasts are also implemented.
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MICHELE, ANELLI. "The price discovery process of the sovereign and bank credit risk in a high-volatility framework." Doctoral thesis, Università di Siena, 2020. http://hdl.handle.net/11365/1095780.
Full textAbstract:
This research study presents three distinct and separate (but logically linked) essays focused on the price discovery
process of credit risk.
The aim of the first essay (working paper n. 1) is to analyse the long lasting dynamic relationship between
the credit default swap (CDS) premia and the government bond spreads (GBS), by focusing particularly on the
sovereign credit risk, in order to evaluate the lead-lag markets in the price discovery process against the backdrop of
a deep crisis. The focus of this study concerns the case of Italy, one of the major countries subject to international
speculative attacks by market operators because of the weak GDP growth, the high public debt and the political
fragility, for the period 2007-2017.
In the second essay (working paper n. 2) the analysis is extended to the lead-lag relationship between the PIIGS - excp Greece
10-year CDS premia and the respective government bond spreads (GBS) series by employing daily data, from January
2007 to October 2017, provided by Bloomberg. The time interval has been considered as whole in the first part
of the analysis, without distinguishing the different stages of development of the recent crisis, while in the second
part I focused on the sovereign debt crisis impact on the lead-lag relationship.
In the third essay (working paper n. 3) It has been evaluated, as a preliminary stage of the investigation, the lead-lag
relationship between the Italian sovereign 5Y CDS premia and the Italian banks proxy 5Y CDS premia series
by employing daily data, for the interval Q2 2007- Q3 2018 (provided by Bloomberg). The latter series was built
up by using the Intesa San Paolo 5y CDS contracts and the Unicredit 5y CDS contracts series weighted by the
respective market capitalization. In the second part of the study, I extended the determinants inspired by the classic Merton (1974 ) model in order to investigate on the drivers of Italian bank credit risk during the most volatile phases of this decade: the financial crisis (August 2007- October 2009 ), the sovereign debt crisis (October 2009 - July 2012 ) and the anti-establishment
Government/pre-Italy’s budget update (March 2018 - September 2018 ) period.
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Bortolini, Rafaela. "Enhancing building performance : a Bayesian network model to support facility management." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/666187.
Full textAbstract:
The performance of existing buildings is receiving increased concern due to the need to renovate the aging building stock and provide better quality of life for end users. The conservation state of buildings and the indoor environment conditions have been related to occupants’ well-being, health, and productivity. At the same time, there is a need for more sustainable buildings with reduced energy consumption.
Most challenges encountered during the analysis of the performance of existing buildings are associated with the complex relationships among the causal factors involved. The performance of a building is influenced by several factors (e.g., environmental agents, occupant behavior, operation, maintenance), which also generate uncertainties when predicting it. Most previous studies that investigate methods to assess a building’s performance do not consider the uncertainty and are often based on linear models.
Although different stakeholders’ requirements regarding building performance coexist, few studies centered on the implications of these requirements. Previous studies tend to be highly specific on indicators related to a particular performance aspect, overlooking potential trade-offs that may occur between them. Therefore, a holistic and integrated approach to manage the performance of existing buildings has not been explored. Facility managers need an efficient approach to deal with uncertainty, to manage risks, and systematically identify, analyze, evaluate and mitigate factors that may impact the building performance.
Taking into account the aforementioned aspects, the aim of this thesis is to devise a Bayesian network (BN) model to holistically manage the operational performance of buildings and support facility management. The proposed model consists of an integrated probabilistic approach to assess the performance of existing buildings, considering three categories: safety and elements working properly, health and comfort, and energy efficiency. The model also provides an understanding of the causality chain between multiple factors and indicators regarding building performance. The understanding of the relationships between building condition, end user comfort and building energy efficiency, supports facility managers to unwind a causal explanation for the performance results in a reasoning process.
The proposed model is tested and validated using sensitivity analysis and data from existing buildings. A set of model applications are discussed, including the assessment of a building’s performance holistically, the identification of causal factors, the prediction of building performance through renovation and retrofit scenarios, and the prioritization of maintenance actions. Case studies also allow to illustrate the applicability of the model for ensuring that its interactions and outcomes are feasible. Scenario analyses provide a basis for a deeper understanding of the potential responses of the model, helping facility managers to optimize operation strategies of buildings in order to enhance its performance.
The results of this thesis also include data collection methods for the inputs of the proposed BN model. A building inspection system is proposed to evaluate the technical performance of buildings, a text-mining approach is developed to analyze maintenance requests of end users, and a questionnaire is formulated to collect end-user satisfaction regarding building comfort. To conclude, this work proposes the use of Building Information Modeling (BIM) to store and access building information, which are typically disperse and not standardized in existing buildings.Actualmente, el desempeño de los edificios existentes es de gran interés debido a la necesidad de renovar el stock de edificios antiguos, proporcionando así una mejor calidad de vida a los usuarios finales. El estado de conservación de los edificios y las condiciones ambientales interiores se relacionan con el bienestar, la salud y la productividad de los ocupantes. Al mismo tiempo, existe la necesidad de edificios más sostenibles con un menor consumo energético. El desempeño de un edificio se ve afectado por varios factores (p.ej., agentes ambientales, comportamiento de los ocupantes, operación, mantenimiento, etc.). La mayoría de estos aspectos y causas muestran complejas relaciones, y consecuentemente existe una gran incertidumbre para predecirlo. Sin embargo, las investigaciones anteriores no contemplan estas relaciones causales y, a menudo, se basan en modelos lineales. Aunque el desempeño de los edificios se debe abordar teniendo en cuenta los requisitos de las diferentes partes interesadas, pocos estudios se centran en este enfoque. Los estudios anteriores tienden a analizar aspectos particulares del desempeño, ignorando las posibles relaciones que pueden ocurrir entre ellos. Los gestores de edificios deben abordar eficientemente la incertidumbre, gestionar los riesgos e identificar, analizar, evaluar y mitigar sistemáticamente los factores que pueden afectar el desempeño del edificio. Teniendo en cuenta los aspectos comentados anteriormente, el objetivo de esta tesis es desarrollar un modelo de red bayesiana (BN) para gestionar holísticamente el desempeño operativo de los edificios y apoyar su gestión. El modelo propuesto consiste en un enfoque probabilístico para evaluar el desempeño de los edificios existentes, considerando tres categorías: seguridad y funcionalidad, salud y confort, y eficiencia energética. El modelo también proporciona una interpretación de la cadena de causalidad entre los múltiples factores e indicadores relacionados con el desempeño del edificio. El análisis de las relaciones entre los diferentes aspectos del desempeño de los edificios (estado de conservación del edificio, el confort del usuario final y la eficiencia energética del edificio) va a permitir explicar y entender sus factores causales y va a posibilitar mejorar la gestión de estos edificios. La verificación del modelo propuesto se lleva a cabo mediante análisis de sensibilidad y datos de edificios existentes. Las aplicaciones del modelo incluyen: la evaluación del desempeño de edificios de forma integrada; la identificación de factores causales; la predicción del desempeño de los edificios a través de escenarios de renovación y modernización; y la priorización de las acciones de mantenimiento. La implementación del modelo en diversos casos de estudio permite ilustrar su aplicabilidad y validar su uso. Los resultados de esta tesis también incluyen métodos de recogida de datos para las variables del modelo propuesto. De hecho, se propone un sistema de inspección de edificios para evaluar el desempeño técnico de los edificios, se desarrolla un sistema de text mining para analizar las solicitudes de mantenimiento de los usuarios finales y se formula un cuestionario para recoger la satisfacción de los usuarios finales en relación a los espacios de los edificios en los que interactúan. Para concluir, este trabajo propone el uso del Building Information Modeling (BIM) para almacenar y acceder a la información necesaria para el modelo.
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Mvita, Mpinda Freddy. "The impact of dividend policy on shareholders' wealth : evidence from the Vector Error Correction Model." Diss., University of Pretoria, 2012. http://hdl.handle.net/2263/31010.
Full textAbstract:
Dividend policy is widely researched in financial management, but determining whether it affects the market price per share is difficult. There has been much published on the subject, which presented theories such as the Modigliani, Miller, Gordon, Lintner, Walter and Richardson propositions and the relevance and irrelevance theories. However, little research has been done on the impact of dividend policy on shareholders’ wealth while considering the short- and long-run effects. The Vector Error Correction Model (VECM) was used to describe the short-run and long-run dynamics or the adjustment of the cointegrated variables towards their equilibrium values in South Africa. This study attempts to explain the effect of dividend policy on the market price per share. A sample of 46 companies listed on the Johannesburg Securities Exchange (JSE) was selected for the period 1995-2010. Three variables were used, namely the market price per share, the dividend per share and the earnings per share. The market price per share was used as a proxy in measuring shareholders’ wealth and the dividend per share was used as a proxy in measuring the dividend policy. Fixed and random effects models were applied to panel data to determine the relation between dividend policy and market price per share. The fixed effects method was used to control the stable characteristics of the companies over a fixed period. The random effects model was applied when the companies’ characteristics differed. Results for both models indicated that dividend yield is positively related to market price per share, while earnings per share do not have a significant impact on the market price per share. To test the strength of the long-run relationship, the VECM was applied. The coefficient for dividend per share in the co-integrating equation was positive, while the coefficient for earnings per share was negative. This confirms previous research findings. The results suggest that there is a long-run relationship between dividend per share and market price per share. The Granger causality test indicates there is bi-directional Granger causality between market price per share and dividend per share in South Africa. Therefore dividend policy does have a significant long-run impact on the share price and therefore provides a signal about the company’s financial success.Dissertation (MCom)--University of Pretoria, 2012.
Financial Management
Unrestricted
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Kilic, Esen. "An Empirical Analysis Of The Relationship Between Financial Deepening And Economic Growth: The Case Of Turkey." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609913/index.pdf.
Full textAbstract:
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.
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Chi, Nam Yau. "Economically justified equity investment strategies capable of withstanding growing interest rate environment." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/18823.
Full textAbstract:
Mestrado em Economia Monetária e FinanceiraThis thesis proposes an approach for selection of stocks that could serve as a natural hedge for fixed income portfolios to minimize rising interest rate risk. The developed approach is applied to the case of US equity markets. Based on macroeconomic analysis, vector autoregressive model and Granger causality tests, and financial analysis, it is concluded that US financial sector is the optimal choice among all sectors that have strong correlations with interest rates. The thesis? results could be useful for interest rate risk management of the investment portfolios under the growing interest rate environment, in particular, and for investment industry professionals.
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Bisová, Sára. "Modely vývoje inflace a její volatility v ČR." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-73484.
Full textAbstract:
This paper focuses on analysing and modelling inflation and its dynamics in Czech Republic applying a special kind of econometric models. Firstly economic theory of inflation is mentioned - fundamental terms, measuring methods of inflation, the way Czech national bank is monitoring the inflation and obviously a short summary of historical evolution of inflation in Czech economy. In the second part of this paper two econometric concepts of modelling time series are introduced - vector autoregression models (VAR models) and volatility models, concretely ARCH and GARCH models. In connection with the VAR models, Granger causality, impulse response functions, cointegration and error correction models are described. The empirical part includes application of selected models on real time series of chosen macroeconomic indicators. The estimation outputs are interpreted and forecasts are implemented. The quality of chosen econometric models for modelling inflation in Czech Republic is discussed.
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Fernandes, Pedro Manuel Ribeiro. "The role of banks in economic growth : an empirical application to Portugal." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/19408.
Full textAbstract:
Mestrado em Economia Monetária e FinanceiraEsta dissertação avalia o contributo dos bancos para o crescimento económico em Portugal desde a adopção do Euro, usando testes de cointegração e causalidade, bem como funções de resposta a impulsos. Usando rácios de passivos líquidos (depósitos) dos bancos e empréstimos em percentagem do PIB nominal como medidas do desenvolvimento financeiro, encontramos forte evidência de que o crescimento económico exerce um impacto positivo no desenvolvimento financeiro, de acordo com Demetriades e Hussein (1996). Concluiu-se também que os empréstimos bancários não aumentam o produto real no longo e no curto prazo, também de acordo com Demetriades e Hussein (1996). Ao invés disso, estes têm um efeito negativo no PIB real per capita. Esses resultados corroboram a visão defendida por Robinson (1952), como citado em King e Levine (1993a) e Lucas (1988), de que o financiamento apenas evolui em resposta aos desenvolvimentos da economia.
This dissertation evaluates the role of banks in economic growth in Portugal since the adoption of the Euro, using cointegration and causality tests, as well as impulse response functions. Using ratios of banks? liquid liabilities (deposits) and loans to nominal GDP as a measure of financial development, we find strong evidence of economic growth exerting a positive impact on financial development, in line with Demetriades and Hussein (1996). It was also concluded that bank lending does not boost real output both in the long-run and in the short-run, also in line with Demetriades and Hussein (1996). Instead, it has a negative effect on real per capita GDP. These results support the view championed by Robinson (1952), as cited in King and Levine (1993a), and Lucas (1988), that finance only evolves in response to developments in the economy.
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FALOTICO, ROSA. "Modelli ad Equazioni Strutturali e Reti Probabilistiche Bayesiane: due approcci a confronto nello studio di relazioni causali." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/19444.
Full textAbstract:
Causality is a concept extremely important in science, but its definition is quite controversial and its detection is not exempt from problems. There are different approaches to deal with causality. Two of them are the Structural Equation Models (SEMs) and the Probabilistic Bayesian Networks (PBNs). SEMs are confirmative models. Given a causal structure, they test if it is coherent with data. In this context they are estimated using the Partial Least Squares Path Modeling technique in order to obtain the scores of latent variables. PBNs are inductive methods. Their attempt is to extract the causal scheme deriving from data, without presupposing any knowledge. Both models presents advantages and disadvantages regardless of the causality approach they refer to. SEMs are best suited for quantitative data and when there is a solid theoretical knowledge on the subject of analysis. PBNs are preferable for nonlinear analysis or uncertain causal scheme.
In the thesis a possible integration of the two methods is proposed in the analysis of data deriving from a satisfaction and customer loyalty survey for “Customer American Satisfaction Index” (ACSI).
Results suggest that the SEMs are more suitable than the PBNs and that the integration of the two statistical models is advantageous only in part. This is related to the kind of data, since the ACSI survey is structured for a PLS-PM analysis. Thus, it could be very interesting repeat the comparison for different types of data.
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Schulz, Christoph. "Causation and the objectification of agency." Thesis, University of Hertfordshire, 2015. http://hdl.handle.net/2299/16480.
Full textAbstract:
This dissertation defends the so-called 'agency-approach' to causation, which attempts to ground the causal relation in the cause's role of being a means to bring about its effect. The defence is confined to a conceptual interpretation of this theory, pertaining to the concept of causation as it appears in a causal judgement. However, causal judgements are not seen as limited to specific domains, and they are not exclusively attributed to human agents alone. As a methodological framework to describe the different perspectives of causal judgments, a method taken from the philosophy of information is made use of - the so-called 'method of abstraction'. According to this method, levels of abstraction are devised for the subjective perspective of the acting agent, for the agent as observer during the observation of other agents' actions, and for the agent that judges efficient causation. As a further piece of propaedeutic work, a class of similar (yet not agency-centred) approaches to causation is considered, and their modelling paradigms - Bayesian networks and interventions objectively construed - will be criticised. The dissertation then proceeds to the defence of the agency-approach, the first part of which is a defence against the objection of conceptual circularity, which holds that agency analyses causation in causal terms. While the circularity-objection is rebutted, I rely at that stage on a set of subjective concepts, i.e. concepts that are eligible to the description of the agent's own experience while performing actions. In order to give a further, positive corroboration of the agency-approach, an investigation into the natural origins and constraints of the concept of agency is made in the central chapter six of the dissertation. The thermodynamic account developed in that part affords a third-person perspective on actions, which has as its core element a cybernetic feedback cycle. At that point, the stage is set to analyse the relation between the first- and the third-person perspectives on actions previously assumed. A dual-aspect interpretation of the cybernetic-thermodynamic picture developed in chapter six will be directly applied to the levels of abstraction proposed earlier. The level of abstraction that underpins judgments of efficient causation, the kind of causation seemingly devoid of agency, will appear as a derived scheme produced by and dependent on the concept of agency. This account of efficient causation, the 'objectification of agency', affords the rebuttal of a second objection against the agency-approach, which claims that the approach is inappropriately anthropomorphic. The dissertation concludes with an account of single-case, or token level, causation, and with an examination of the impact of the causal concept on the validity of causal models.
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Nakatani, Tomoaki. "Four Essays on Building Conditional Correlation GARCH Models." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-952.
Full textAbstract:
This thesis consists of four research papers. The main focus is on building the multivariate Conditional Correlation (CC-) GARCH models. In particular, emphasis lies on considering an extension of CC-GARCH models that allow for interactions or causality in conditional variances. In the first three chapters, misspecification testing and parameter restrictions in these models are discussed. In the final chapter, a computer package for building major variants of the CC-GARCH models is presented. The first chapter contains a brief introduction to the CC-GARCH models as well as a summary of each research paper. The second chapter proposes a misspecification test for modelling of the conditional variance part of the Extended Constant CC-GARCH model. The test is designed for testing the hypothesis of no interactions in the conditional variances. If the null hypothesis is true, then the conditional variances may be described by the standard CCC-GARCH model. The test is constructed on the Lagrange Multiplier (LM) principle that only requires the estimation of the null model. Although the test is derived under the assumption of the constant conditional correlation, the simulation experiments suggest that the test is also applicable to building CC-GARCH models with changing conditional correlations. There is no asymptotic theory available for these models, which is why simulation of the test statistic in this situation has been necessary. The third chapter provides yet another misspecification test for modelling of the conditional variance component of the CC-GARCH models, whose parameters are often estimated in two steps. The estimator obtained through these two steps is a two-stage quasi-maximum likelihood estimator (2SQMLE). Taking advantage of the asymptotic results for 2SQMLE, the test considered in this chapter is formulated using the LM principle, which requires only the estimation of univariate GARCH models. It is also shown that the test statistic may be computed by using an auxiliary regression. A robust version of the new test is available through another auxiliary regression. All of this amounts to a substantial simplification in computations compared with the test proposed in the second chapter. The simulation experiments show that, under both under both Gaussian and leptokurtic innovations, as well as under changing conditional correlations, the new test has reasonable size and power properties. When modelling the conditional variance, it is necessary to keep the sequence of conditional covariance matrices positive definite almost surely for any time horizon. In the fourth chapter it is demonstrated that under certain conditions some of the parameters of the model can take negative values while the conditional covariance matrix remains positive definite almost surely. It is also shown that even in the simplest first-order vector GARCH representation, the relevant parameter space can contain negative values for some parameters, which is not possible in the univariate model. This finding makes it possible to incorporate negative volatility spillovers into the CC-GARCH framework. Many new GARCH models and misspecification testing procedures have been recently proposed in the literature. When it comes to applying these models or tests, however, there do not seem to exist many options for the users to choose from other than creating their own computer programmes. This is especially the case when one wants to apply a multivariate GARCH model. The last chapter of the thesis offers a remedy to this situation by providing a workable environment for building CC-GARCH models. The package is open source, freely available on the Internet, and designed for use in the open source statistical environment R. With this package can estimate major variants of CC-GARCH models as well as simulate data from the CC-GARCH data generating processes with multivariate normal or Student's t innovations. In addition, the package is equipped with the necessary functions for conducting diagnostic tests such as those discussed in the third chapter of this thesis.Diss. Stockholm : Handelshögskolan, 2010. Sammanfattning jämte 4 uppsatser.
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Alshogeathri, Mofleh Ali Mofleh. "Macroeconomic determinants of the stock market movements: empirical evidence from the Saudi stock market." Diss., Kansas State University, 2011. http://hdl.handle.net/2097/11989.
Full textAbstract:
Doctor of PhilosophyDepartment of Economics
Lance J. Bachmeier
This dissertation investigates the long run and short run relationships between Saudi stock market returns and eight macroeconomic variables. We investigate the ability of these variables to predict the level and volatility of Saudi stock market returns. A wide range of Vector autoregression (VAR) and generalized autoregressive conditional heteroskedasticity (GARCH) models estimated and interpreted. A Johansen-Juselius cointegration test indicates a positive long run relationship between the Saudi stock price index and the M2 money supply, bank credit, and the price of oil, and a negative long run relationship with the M1 money supply, the short term interest rate, inflation, and the U.S. stock market. An estimated vector error correction model (VECM) suggests significant unidirectional short run causal relationships between Saudi stock market returns and the money supply and inflation. The VECM also finds a significant long run causal relationship among the macroeconomic variables in the system. The estimated speed of adjustment indicates that the Saudi stock market converges to the equilibrium within half a year. Granger causality tests show no causal relationship between Saudi stock market returns and the exchange rate. Impulse response function analysis shows no significant relationship between Saudi stock market returns and the macroeconomic variables. Forecast error variance decompositions suggest that 89% of the variation in Saudi stock market returns is attributable to its own shock, which implies that Saudi stock market returns are largely independent of the macroeconomic variables in the system. Finally, a GARCH-X model indicates a significant relationship between volatility of Saudi stock returns and short run movements of macroeconomic variables. Implications of this study include the following. (i) Prediction of stock market returns becomes more difficult as the volatility of the macroeconomic variables increases in the short run. (ii) Investors should look at the systematic risks revealed by these macroeconomic variables when structuring their portfolios and diversification strategies. (iii) Policymakers should seek to minimize macroeconomic fluctuations considering the effect of macroeconomic variables changes on the stock market when formulating economic policy.
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Rafiq, Shuddhasattwa. "Oil consumption, pollutant emission, oil proce volatility and economic activities in selected Asian Developing Economies." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/693.
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It is now well established in the literature that oil consumption, oil price shocks, and oil price volatility may impact the economic activities negatively. Studies identifying the relationship between energy and/or oil consumption and output primarily take two different approaches. One approach includes energy or oil consumption in addition to output, labour, and capital. The other approach takes energy and/or oil, output and prices. Based on these two models most of the previous studies suggest energy conservation policies for different economies. However, none of the previous studies considered both of these models jointly to make policy implications and there are not many studies investigating oil consumption-output relationship in a multivariate model in the context of developing economies. Furthermore, one of the important variables in making any conservation policies, carbon emission, is omitted from the models.Similarly, there has been a large body of literature investigating the impact of oil price shocks in different economies. Nevertheless, studies analysing the impact of oil price volatility on economic activities are very limited. More importantly, studies analysing the impact of oil price volatility in developing economies are almost non-existent. In the light of increasing demand for oil from the developing nations, comprehensive studies on identifying the impact of oil consumption, oil prices, and oil price volatility on developing economies is warranted.Hence, in this thesis, the contribution of oil in economic development is investigated with the help of two different models. The first model, termed as supply-side approach, analyses the contribution of oil consumption in economic activities within the traditional production function framework. The second model, termed as demand-side approach, analyses the contribution of energy consumption in economic activities in two stages. In the first stage, oil consumption demand is analysed by a tri-variate model having oil prices as the third variable in addition to oil consumption and GDP. In the second stage, carbon emission output is determined in a tri-variate model with carbon emission as the third variable along with oil consumption and output. This thesis also performs a unique task of analysing the impact of volatility on world crude oil prices on the economic activities of six Asian developing economies.With respect to the oil consumption-output relationship, despite dissimilarities in results for causality relationships between oil consumption and output in three different models for different countries, one common result emerges. Except for the Philippines, all other countries are found to be oil dependent either from supply-side or from demand-side or from both of the sides. This implies that for all the considered developing economies, except for the Philippines, oil conservation policies seem to be harder to implement as that may retard their economic growth. In addition to that, one very important findings of the empirical analysis based on the equation regarding pollutant emission output is that for all the countries, except for Malaysia, output Granger causes pollutant emission (CO2) both in the short run and long run.With respect to the impact of oil price volatility on economies, this study finds that oil price volatility seems to impact all the economies in the short run. According to the results, oil price volatility affects GDP growth in China and Malaysia, GDP growth and inflation in India and Indonesia, while in the Philippines volatility in oil prices impacts inflation. However, in Thailand the impact channels are different for pre- and post-Asian financial crisis period. For Thailand, it can be inferred that oil price volatility impacts output growth for the whole period; however, after the Asian financial crisis the impact seems to disappear.Based on the comprehensive study within three different theoretical frameworks the policy implications regarding oil consumption-output relationship can be summarised as follows. For the Philippines, where uni-directional causality from income to oil consumption is found, she may contribute to the fight against global warming directly implementing energy conservation measures. The direction of causality indicates that the oil conservation policies can be initiated with little or no effect on economic growth. For rest of the oil dependent countries where either bidirectional causality or uni-directional causality from oil consumption to output is found in any of the models, since oil is a critical determinant of economic growth in these countries, limiting its use may retard economic growth. Nevertheless, all of these countries may initiate environmental policies aimed at decreasing energy intensity, increasing energy efficiency, and developing a market for emission trading. These countries can invest in research and development to innovate technology that makes alternative energy sources more feasible, thus mitigating pressure on the environment.According to the impact analysis of oil price volatility on economic activities, the policy implications are as follows. In Thailand, the results after the financial crisis show that adverse effect of oil price volatility has been mitigated to some extent. It seems that oil subsidization of the Thai government by introduction of the oil fund and the flexible exchange rate regime plays a significant role in improving economic performance by lessening the adverse effect of oil price volatility on macroeconomic indicators. For all other countries, the impact of oil price volatility is also of short term. Hence, the short-term impact of oil price volatility on the concerned economies may be exerted though the uncertainty born by the fluctuations in the crude oil price in the world market. As far as the impact on GDP growth is concerned, the short-run impact may also be transmitted through the investment uncertainties resulting from increased volatility in oil prices. However, from the Thai experience it can be inferred that flexible exchange rate regime insulate the economy in the short run from any adverse impact from oil price volatility on growth. Hence, it can be suggested that good subsidization policy with considerable knowledge on international currency market, both spot and future, may shield the economies from adverse consequences due to the fluctuation in oil prices in the short run. Nevertheless, this may affect other sectors of the economy like, inflation, interest rate, government budget deficit, etc.
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Melcher, Ota. "Spekulační aktivita na trhu s ropou a její vliv na cenu komodity." Doctoral thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-261935.
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This study aims to analyse the precrisis period on the oil markets with a primary objective of assessing the role of speculation in the commodity's price development and its volatility. First it depicts the rapidly increasing speculative activity on the futures market together with the parallel oil price surge. The speculation is initially proxied by non-commercial traders' positions and subsequently quantified by Working's T-index. The paper then uses speculative traders' positions and both spot and futures prices to test for Granger causality within the framework of VAR models. For the sake of consistency it also evaluates causal links between speculation and inventories level. Further the study investigates the speculation impact on volatility of oil prices by employing various approaches in volatility quantification including GARCH models. Contrary to expectations we find that the speculatio's impact on both prices and their volatility is rather insignificant. In the last chapter we therefore seek for an explanation of the oil price developments by examining the market fundamentals. The interaction of supply and demand finally gives substantial evidence for understanding the price developments in the precrisis period.
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Golubeva, Ana. "Ekonometrinis Baltijos šalių bendrojo vidaus produkto modeliavimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2012. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120723_102646-72088.
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Baigiamajame magistro darbe yra nagrinėjamas Baltijos šalių – Lietuvos, Latvijos ir Estijos BVP, jo kitimo tendencijos bei pagrindiniai makroekonomikos rodikliai – galutinio vartojimo išlaidos, prekių ir paslaugų importas bei eksportas, investicijos, užimtųjų darbo rinkoje skaičius bei BVP defliatorius. Išnagrinėti šių rodiklių apibrėžimai bei ekonominė prasmė, taip pat apžvelgta sukaupta mokslininkų patirtis modeliuojant juos. Siekiant išsiaiškinti ryšius tarp šių rodiklių atlikta koreliacijų bei Grangerio priežastingumo analizė. Modeliuojant, visų pirma, rasti ilgalaikiai sąryšiai tarp kintamųjų, o po to kiekvienai šaliai specifikuotas paklaidų korekcijos modelis bei įvertintas šio modelio tikslumas. Išnagrinėjus praktinius ir teorinius aspektus, pateikiamos baigiamojo darbo išvados ir pasiūlymai. Darbą sudaro 5 dalys: įvadas, analitinė - metodinė dalis, tiriamoji dalis, išvados ir pasiūlymai, literatūros sąrašas. Darbo apimtis – 112 p. teksto be priedų, 60 iliustr., 35 lent., 28 bibliografiniai šaltiniai. Atskirai pridedami darbo priedai.The gross domestic product of the Baltic States – Lithuania, Latvia and Estonia, has been examined in the master thesis. Trends of the GDP and the main macroeconomic indicators – gross final consumption expenditure, imports and exports of goods and services, investment, labor force and GDP deflator have been analyzed. The definitions of these indicators and an economic sense, as well as researchers' experience in modeling, have been examined. In order to establish the relationship between these variables, analysis of the correlation and Granger causality test has been performed. In particular, modeling started with the finding of the long – term relationship between selected indicators. After that the error correction model has been specified and the accuracy of this model has been estimated. After the examination of the practical and theoretical aspects, the conclusions and recommendations have been presented. Structure: introduction, analytical – methodical part, research part, conclusions and suggestions, references. Thesis consists of: 112 p. text without appendixes, 60 pictures, 35 tables, 28 bibliographical entries. Appendixes included.
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Hou, Xiaofang, and Weirui Xu. "The Impact of Overseas Stock Markets on Chinese Stock Markets at the Background of Financial Crises : From the Perspective of Price Index." Thesis, Umeå universitet, Företagsekonomi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-82853.
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Khalil, Rosette. "Finance alternative : quels sont les avantages?" Thesis, Pau, 2021. http://www.theses.fr/2021PAUU2090.
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L’Investissement Socialement Responsable (ISR) qui est qualifié d’investissement « éthique », « vert » ou « durable » est établi sur un principe similaire qui repose sur le principe des investissements ESG. Ainsi, la finance islamique, à travers le filtrage sectoriel qu’elle impose, représente une option d’investissement socialement responsable intéressante. On considère qu’à travers le développement durable, les objectifs de l’ISR et de la finance islamique sont convergents. Créé en Janvier 2009, par « Satoshi Nakamoto », de nombreuses devises virtuelles comme Bitcoin sont fortement intéressés à faire partie du portefeuille de services du système financier islamique.La thèse est divisée en quatre chapitres. Dans le premier chapitre, nous illustrons l’histoire et l’expansion de la finance islamique dans le monde entier. Nous montrons la croissance de la finance islamique dans les pays musulmans et les pays non musulmans également. Nous mentionnent également les principales transactions appliquées par les institutions financières islamiques et qui sont fondées sur la loi islamique « Shariah ». Nous mentionnons en conséquence de manière simplifiée les articles interdits dans l’Islam.Dans le deuxième chapitre, nous étudions l’efficacité de 41 banques islamiques pures opérant dans 5 pays du CCG pour la période 2004 et 2017. Nous évaluons la rentabilité de nos banques en tenant compte de trois intrants et de trois extrants. Nous comptons sur deux orientations différenciées en termes de contraintes : orientation des entrées et orientation des sorties. Pour ce faire, nous nous appuyons sur la méthode du coût stochastique frontière et de l’enveloppe des données. De nos résultats, nous voyons que les banques islamiques opérant dans la région du CCG ne fonctionnent pas sur la frontière des coûts efficaces peut-être en raison de l’inefficacité de la gestion et de l’utilisation abusive des facteurs de production. L’utilisation d’une approche axée sur la production ne modifie pas de façon significative les résultats obtenus. Dans ce contexte, les résultats ont montré que les scores d’efficacité ne pouvaient pas être expliqués uniquement par des ratios financiers, car ils sont liés à des facteurs externes correspondant à l’inefficacité X et à l’environnement économique.Dans le troisième chapitre, nous étudions les caractéristiques de Bitcoin comme monnaie virtuelle par rapport à quatre indices islamiques. Nous nous appuyons sur les modèles de la famille Garch pour détecter le niveau et la persistance de la volatilité pendant la période de 2010 à 2018. Nous comptons également sur le modèle de commutation de Markov pour étudier la durée de persistance des indices pendant le régime à faible risque et le régime à haut risque. De nos résultats, nous remarquons que les indices islamiques et Bitcoin ne sont pas immunisés contre les chocs financiers. Cependant, la persistance de la volatilité du Bitcoin est plus importante que le cas du marché boursier islamique. En outre, nous confirmons le rôle de Bitcoin comme couverture pendant les moments normaux et comme refuge pendant les moments d’anxiété.Dans le quatrième chapitre, nous étudions l’interaction entre trois indices islamiques et leurs homologues durables. Nous appliquons le modèle de décalage réparti autorégressif pour voir l’existence de la relation à court et à long terme entre indices. Dans la deuxième étape, nous utilisons la causalité de fréquence de domaine pour étudier la causalité dynamique et sa directe entre chaque indice islamique et sa contrepartie. Nos résultats montrent l’existence d’un équilibre à long terme et la position des marchés boursiers comme compléments principalement à court terme et substituts à long terme. Les résultats de causalité « fréquence par fréquence » montrent l’existence d’une relation de causalité à court terme entre les trois marchés boursiers viables et leurs homologues islamiquesSocially Responsible Investing (SRI) which is described as “ethical”, “green” or “sustainable” investing is established on a similar principal which is based on the principle of ESG investments. Thus, Islamic finance, through the sector filtering it imposes, represents an interesting socially responsible investment option. It is considered that through sustainable development, the objectives of SRI and Islamic finance are converged. Created in January 2009, by “Satoshi Nakamoto”,many virtual currencies like Bitcoin are strongly interested to be a part of the services portfolio of the Islamic Financial system.The thesis is divided into four chapters. In the first chapter, we illustrate the history and the expansion of Islamic finance worldwide. We show the growth in terms of Islamic finance in Muslim countries and non-Muslim countries as well. Wealso mention the main transactions applied by Islamic financial institutions and which are based on the Islamic law “Shariah”. We mention accordingly in a simplified manner the prohibited items in Islam.In the second chapter, we study the efficiency of 41 pure Islamic banks operating in in 5 GCC countries for the period 2004 and 2017. We estimate the cost efficiency of our banks by considering three inputs and three outputs. We rely on twoorientations which differentiate in terms of constraints: input orientation and output orientation. In order to do this, we rely on the cost stochastic frontier and data envelopment method. From our results, we see that the Islamic banks operating in the GCC region do not operate on the efficient cost frontier maybe due to managerial inefficiency and misuse of production factors. The use of the output-oriented does not change the obtained results significantly. In this context, the results showed that the efficiency scores could not be explained solely by financial ratios, as they are related to external factors corresponding to the X-inefficiency and economic environment.In the third chapter, we study the characteristics of Bitcoin as a virtual currency versus four Islamic indices. We rely on Garch family models to detect the level and the persistence of volatility during the period 2010 until 2018. We also rely onthe Markov switching model to study the duration of persistence of the indices during low risk regime and high risk regime. From our results, we notice that Islamic indices and Bitcoin are not immune to financial shocks. However, thevolatility persistence of Bitcoin is more important than the case of Islamic stock market. In addition, we confirm the role of Bitcoin as a hedge during normal moments and as a safe haven during moment of anxiety.In the fourth chapter, we study the interaction between three Islamic indices versus their sustainable counterparts. We apply the autoregressive distributed lag model to see the existence of the short-run and long-run relationship between theindices. In the second step, we use the Domain frequency causality to study the dynamic causality and its directness between each Islamic index and its counterpart. Our results show the existence of a long-run equilibrium and the position of the stock markets as complements mainly on the short term and substitutes on the long-term. The “frequency-byfrequency” causality outputs show the existence of a causal relationship on the Short-term between the three sustainable stock market and their Islamic counterparts
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Keir, Warren Neill. "Voter behaviour and constitutional change in Australia since 1967." Thesis, Queensland University of Technology, 2009. https://eprints.qut.edu.au/31139/1/Warren_Keir_Thesis.pdf.
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Australian Constitutional referendums have been part of the Australian political system since federation. Up to the year 1999 (the time of the last referendum in Australia), constitutional change in Australia does not have a good history of acceptance. Since 1901, there have been 44 proposed constitutional changes with eight gaining the required acceptance according to section 128 of the Australian Constitution. In the modern era since 1967, there have been 20 proposals over seven referendum votes for a total of four changes. Over this same period, there have been 13 federal general elections which have realised change in government just five times. This research examines the electoral behaviour of Australian voters from 1967 to 1999 for each referendum. Party identification has long been a key indicator in general election voting. This research considers whether the dominant theory of voter behaviour in general elections (the Michigan Model) provides a plausible explanation for voting in Australian referendums. In order to explain electoral behaviour in each referendum, this research has utilised available data from the Australian Electoral Commission, the 1996 Australian Bureau of Statistics Census data, and the 1999 Australian Constitutional Referendum Study. This data has provided the necessary variables required to measure the impact of the Michigan Model of voter behaviour. Measurements have been conducted using bivariate and multivariate analyses. Each referendum provides an overview of the events at the time of the referendum as well as the =yes‘ and =no‘ cases at the time each referendum was initiated. Results from this research provide support for the Michigan Model of voter behaviour in Australian referendum voting. This research concludes that party identification, as a key variable of the Michigan Model, shows that voters continue to take their cues for voting from the political party they identify with in Australian referendums. However, the outcome of Australian referendums clearly shows that partisanship is only one of a number of contributory factors in constitutional referendums.
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Sanchez, Roberto. "Application des Bond graphs à la modélisation et à la commande de réseaux électriques à structure variable." Phd thesis, Ecole Centrale de Lille, 2010. http://tel.archives-ouvertes.fr/tel-00690633.
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Cette thèse étudie les problèmes liés à l'association des principaux composants des réseaux électriques.La nature inductive des éléments à connecter pose des problèmes lors de leur association dans un nœud de connexion commun. Deux solutions sont proposées pour résoudre ce problème et rendre ainsi possible la simulation. Une première solution accepte la présence de causalités dérivées, la deuxième consiste à simplifier les modèles en supprimant localement les régimes dynamiques pour faciliter leur association.La mise en évidence graphique de la causalité dans le modèle global d'un micro réseau à structure variable montre que différentes configurations sont possibles, avec pour chacune un comportement et un fonctionnement différents pour les composants. L'outil bond graph a été choisi pour la modélisation des différents éléments, l'analyse des propriétés des modèles et la conception de lois de commande par modèle inverse à l'aide de la bicausalité. La robustesse de la commande pour le convertisseur d'électronique de puissance est analysée d'une manière classique pour tester ses performances par rapport aux incertitudes paramétriques, en faisant varier la charge connectée au convertisseur. La commande est validée par simulation et de manière expérimentale.
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Gil, Vera Carina Lopes Gonçalves. "Impacto do preço do petróleo no mercado accionista dos Estados Unidos, França, Holanda, Bélgica e Portugal : análise por sector de actividade." Master's thesis, Instituto Superior de Economia e Gestão, 2011. http://hdl.handle.net/10400.5/10189.
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Mestrado em FinançasA presente investigação que contribui para o conhecimento da relação entre o preço do petróleo e o retorno do mercado accionista norte-americano estruturando-se em torno das seguintes questões: (1) As variações do preço do petróleo têm impacto no retorno do mercado accionista?; (2) As variações do preço do petróleo têm impacto no retorno dos sectores?; (3) Quando existem efeitos estes são assimétricos?; e (4) Existe causalidade de Granger? Usando dados do DataSream Advance para o período de 1 de Janeiro de 2000 a 31 de Março de 2011 de dez sectores de actividade do índice S&P 500 e do preço do Petróleo (WTI) foi estimado o modelo de mercado (por sectores) e o modelo de preços de dois factores (mercado e petróleo). Testou-se a assimetria entre as variáveis, assim como a Causalidade de Granger. Conclui-se através do modelo de mercado que o índice S&P 500 explica as variações dos sectores. Quando introduzida a variável designada por a variação inesperada no preço do petróleo e aplicado o modelo de dois factores verifica-se a existência de relação entre as variações do preço do petróleo e alguns sectores. Os sectores que apresentam uma associação positiva são o da Energia e o dos Materiais e uma associação negativa os sectores da Saúde, Consumo Básico, Telecomunicações e Consumo Discricionário. Em relação à existência de efeitos assimétricos os testes efectuados permitem concluir pela existência de simetria entre o impacto das variações do preço petróleo e as rendibilidade sectoriais.
This research contributes to the knowledge of the relationship between oil prices and the return on U.S. stock market. The main research questions are: (1) Do changes in oil prices have an impact on overall stock market returns?; (2) Do changes in oil prices impact on sectorial stock market returns?; (3) When there are effects, are they asymmetrical?; and (4) Is there evidence for Granger causality? The research uses DataStream Advance 4.0 data for the period between the 1 January 2000 and 31 March 2011, for oil price (WTI) and ten activity sectors (S&P 500 index). Market models (by sector) and Two Factor ?market and oil? Princing Model are estimated. The asymmetry effects between the variables, as well as the Granger Causality are also studied. It is concluded through the market model that the S&P 500 index explains the variations of the sectors. A strong relation between the oil price variations and the returns on some sectors are found when an expected variation in oil price is considered and the Two Factors model is applied. Energy and Materials present a positive association while Health Care, Consumer Staples, Telecommunications and Consumer Discretionary present a negative association. Regarding the existence of asymmetric effects, tests provide evidence that there is symmetry between the impact of oil price variations and the sector returns. Concerning the Granger Causality Test, the only significant relationship found between oil prices and the return on the sectors was for the Telecommunications sector and only from the eighth week on.
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Prague, Mélanie. "Utilisation des modèles dynamiques pour l'optimisation des traitements des patients infectés par le VIH." Thesis, Bordeaux 2, 2013. http://www.theses.fr/2013BOR22056.
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La plupart des patients infectés par le VIH ont une charge virale qui peut être rendue indétectable par des combinaisons antirétrovirales hautement actives (cART); cependant, il existe des effets secondaires aux traitements. L'utilisation des modèles mécanistes dynamiques basés sur des équations différentielles ordinaires (ODE) a considérablement amélioré les connaissances de la dynamique HIV-système immunitaire et permet d'envisager une personnalisation du traitement. L'objectif de ces travaux de thèse est d'améliorer les techniques statistiques d'estimation de paramètres dans les modèles mécanistes dynamiques afin de proposer des stratégies de surveillance et d'optimisation des traitements. Après avoir introduit NIMROD un algorithme d'estimation bayésienne basé sur une maximisation de la vraisemblance pénalisée, nous montrons la puissance des approches mécanistes dynamiques pour l'évaluation des effets traitements par rapport aux méthodes descriptives d'analyse des trajectoires des biomarqueurs. Puis, nous définissons le « modèle à cellules cibles », un système ODE décrivant la dynamique du VIH et des CD4. Nous montrons qu'il possède de bonnes capacités prédictives. Nous proposons une preuve de concept de la possibilité de contrôler individuellement la dose de traitement. Cette stratégie adaptative réajuste la dose du patient en fonction de sa réaction à la dose précédente par une procédure bayésienne. Pour finir, nous introduisons la possibilité de l’'individualisation des changements de cART. Ce travail passe par la quantification in vivo d'effets de cART en utilisant des indicateurs d'activité antivirale in vitro. Nous discutons la validité des résultats et les étapes méthodologiques nécessaires pour l'intégration de ces méthodes dans les pratiques cliniquesMost HIV-infected patients viral loads can be made undetectable by highly active combination of antiretroviral therapy (cART), but there are side effects of treatments. The use of dynamic mechanistic models based on ordinary differential equations (ODE) has greatly improved the knowledge of the dynamics of HIV and of the immune system and can be considered for personalization of treatment. The aim of these PhD works is to improve the statistical techniques for estimating parameters in dynamic mechanistic models so as to elaborate strategies for monitoring and optimizing treatments. We present an algorithm and program called NIMROD using Bayesian inference based on the maximization of the penalized likelihood. Then, we show the power of dynamic mechanistic approaches for the evaluation of treatment effects compared to methods based on the descriptive analysis of the biomarkers trajectories. Next, we build the “target cells model “, an ODE system of the dynamics between the HIV and CD4. We demonstrate it has good predictive capabilities. We build a proof of concept for drug dose individualization. It consists in tuning the dose of the patient based on his reaction to the previous doses using a Bayesian update procedure. Finally, we introduce the possibility of designing an individualized change of cART. This work involves the quantification of in vivo effects of cART using in vitro antiviral activity indicators. We discuss the validity of the results and the further steps needed for the integration of these methods in clinical practice
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Gonçalves, Carlos Aurélio Bustamante. "O mercado de caminhões no Brasil: um estudo econométrico dos determinantes das vendas de veículos." reponame:Repositório Institucional do FGV, 2016. http://hdl.handle.net/10438/17541.
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Este estudo trata do comportamento da demanda por caminhões novos no Brasil no período de 1996 a 2015 e da investigação dos fatores que a influenciam. Tal questão é relevante devido à escassez de estudos acerca deste tema, ainda que se trate do modo historicamente predominante de transporte de carga no país. O objetivo de pesquisa é determinar e quantificar os fatores que provocam o aumento ou diminuição das vendas de caminhão no Brasil. Para atingir este objetivo, foram construídos modelos econométricos a partir de dados secundários. Proxies utilizadas em outros modelos de demanda automotiva foram confirmadas e refinadas, enquanto novas proxies foram introduzidas com sucesso. Quanto aos resultados, este estudo inovou ao identificar três tipos de determinantes, e ao detalhar os efeitos e defasagens de suas influências: variáveis relacionadas especificamente ao mercado de caminhões, variáveis relacionadas ao PIB e variáveis relacionadas à confiança do comprador. Adicionalmente, realizou-se uma verificação da causalidade entre crédito e vendas, com o surpreendente resultado de que a influência ocorre no sentido de vendas para crédito. Com estes resultados, este estudo dissemina o conhecimento a respeito do comportamento do mercado a toda a cadeia produtiva, melhorando a qualidade das decisões e proporcionando aumento da eficiência para o sistema como um todo.
This is a study on the demand for new trucks in Brazil from 1996 to 2015, and an investigation on the factors that influence it. This topic is relevant due to the scarcity of studies concerning the subject, and due to the overwhelming domination of trucks in cargo transport in Brazil. It aims identify and quantify the variables that drive the sales of trucks. To reach this goal, econometric models were constructed based on secondary data. Variables usually adopted in other studies on automotive demand were confirmed and even refined and new variables were successfully introduced. This study innovates by identifying three groups of variables, and by detailing the effects and the lags of their influence: variables specific to the truck market, variables related to GDP, and variables related to the decision maker’s confidence. Additionally, a causality analysis involving credit and truck sales was performed, unexpectedly resulting in sales causing credit. Through these results, this study disseminates knowledge about the behavior of the truck market to the entire productive chain, contributing to evolve the quality of decisions and the efficiency of the entire system.
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Ben-David, Shoham. "Applications of Description Logic and Causality in Model Checking." Thesis, 2009. http://hdl.handle.net/10012/4485.
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Model checking is an automated technique for the verification of finite-state systems that is widely used in practice.
In model checking, a model M is verified against a specification $\varphi$, exhaustively checking that the tree of all computations of M satisfies $\varphi$.
When $\varphi$ fails to hold in M, the negative result is accompanied
by a counterexample: a computation in M that demonstrates the failure.
State of the art model checkers apply Binary Decision Diagrams(BDDs) as well as satisfiability solvers for this task. However, both methods suffer from the state explosion problem, which restricts the application of model checking to only modestly sized systems. The importance of model checking makes it worthwhile to explore
alternative technologies, in the hope
of broadening the applicability
of the technique to a wider class of systems.
Description Logic (DL) is a family of knowledge representation formalisms based on decidable fragments of first order logic.
DL is used mainly for designing ontologies in information systems. In recent years several DL reasoners have been developed, demonstrating an impressive capability to cope with very large ontologies.
This work consists of two parts. In the first we harness the growing ability of DL reasoners to solve model checking problems.
We show how DL can serve as a natural setting for representing and solving a model checking problem, and present a variety of
encodings that translate such problems into consistency queries in DL.
Experimental results, using the Description Logic reasoner FaCT++, demonstrate that for some systems and properties, our method can
outperform existing ones.
In the second part we approach a different aspect of model checking. When a specification fails to hold in a model and a counterexample is presented to the user, the counterexample may itself be complex and difficult to understand. We propose an automatic technique to find the computation steps and their associated variable values, that are of particular importance in generating the counterexample. We use the notion of causality to formally define a set
of causes for the failure of the specification on the given counterexample. We give a linear-time algorithm to detect
the causes, and we demonstrate how these causes can be presented to the user as a visual explanation of the failure.
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Tsai, Min-hsiang, and 蔡名翔. "Gray Multi-Attribute Decision Model of Sapphire Polishing process parameter optimization." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/02976720793041300879.
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Dai, Ru-Mei, and 戴如美. "The Impact of Model Assumption for Analyzing the Causality between Variables." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/02048644163171381980.
Full textAbstract:
碩士國立交通大學
統計學研究所
93
In daily life or biological gene, there always exists variables which inference other variables or are influenced by some others. In this paper, our main goal is to analyze the variables which have causality by using statistical methods, to determine the directionality among causality graphs, and to find out the impact of model assumption on those methods. In this field, lots of scientists and statisticians have proposed several methods, for example, linear models (D’haeseleer et al., 1999), nonlinear models (Weaver et al., 1999), and Boolean networks (Kauffman 1993, Somogyi and Sniegoski, 1996), etc. However, there should be some assumptions in all of these models. Murphy and Mian (1998) and Friedman et al. (1999) have suggested that use Bayesian network models of gene expression networks to get some improvements. In this paper, we discuss the concept of Bayesian’s method and using likelihood functions to analyze the causality between two and three variables. We hope to determine the direction between variables.
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Chung, Yi-Ru, and 莊鐿茹. "Predicting Stock Returns with Investor Sentiment—Using Bootstrap Panel Granger Causality Model." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/49163825524138084295.
Full textAbstract:
碩士嶺東科技大學
企業管理系碩士在職專班
103
This paper investigates potential Granger causality between the Investor Sentiment and Stock Returns in 20 stock markets for the period between 2000 and 2013. A new panel-data approach developed in Kónya(2006) which is based on SUR systems and Wald tests with country specific bootstrap critical values is employed in the study. The empirical results indicate that there are four results of causality relationship between Investor Sentiment and Stock Returns, such as(1) Investor Sentiment Granger causes Stock Returns, (2) Stock Returns Granger causes Investor Sentiment, (3) evidence of effects between Investor Sentiment and Stock Returns, and (4)no evidence of effects between Investor Sentiment and Stock Returns. If we examine the next year’s performance, we find “(2) Stock Returns Granger causes Investor Sentiment” is greater than “(4)no evidence of effects between Investor Sentiment and Stock Returns”, which is greater than “(3) evidence of effects between Investor Sentiment and Stock Returns”, which is greater than“(1) Investor Sentiment Granger causes Stock Returns”
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"Using a model of human cognition of causality to orient arcs in structural learning." GEORGE MASON UNIVERSITY, 2009. http://pqdtopen.proquest.com/#viewpdf?dispub=3343811.
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Shao, Pei-chiang, and 邵培強. "A Study on the Causality between the Signals of Neurons by the Autoregressive Model." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/27459996057994492040.
Full textAbstract:
碩士國立中央大學
數學研究所
99
In this study, we take the neural data which recorded signals from anterior cingulate cortex (ACC) and striatum (STR) during the period of acute quinpirole administration in anesthetized rats as an example, to make inferences on the connections between neurons by determining causality in time series. The results show that, (1) The neurons in ACC were linked before quinpirole administration, and there was a steady increase in the intensity of these linkage after quinpirole administration. (2) There were no significant causal relationships between STR neurons before nor after quinpirole administration.(3) There were no significant causal relationships between ACC and STR neurons before quinpirole administration, but information flows from ACC to STR arose after quinpirole administration. Because of the low intensity of these information flows, we conjecture that the connections between ACC and STR neurons are mediated by some undetected neurons. Finally, neurons were classified into "source", "middle" and "target" three groups according to the order of information delivery. And we construct individually a neural subnetwork before and after quinpirole administration.
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Liu, Yong-Ting, and 劉詠庭. "The Price-Volume Variance Causality Test on the Chinese Stock Market- EC-GARCH Model." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/00702570433708976826.
Full textAbstract:
碩士國立臺北大學
國際企業研究所
100
This study investigates on the variance causality by applying the Exponential Causality multivariate GARCH (EC-GARCH)model, which was introduced by Massimiliano Caporin in 2007. The main structure of this model is an exponential factor multiplying the traditional GARCH equation to drive the causality relation. This research mainly focuses on the biggest stock exchange of China, selecting return and trading volume of both Shanghai Stock Exchange A Share Index and Shenzhen Stock Exchange A Share Index as our four variables. In addition, used data is weekly data from January 5, 1996 to April 6, 2012 with total 818 observations for each variable. Our purpose is to analyze the variance causality among four variables to provide some useful information for the traders. As the result, by testing on the variance causality between Shanghai Stock Exchange A Share Index and Shenzhen Stock Exchange A Share Index, we find out an unexpected return volatility shock at time t-1 will induce the investors to invest on the stock at the time. The results emphasize the importance of return volatility on predicting the volume change of Shenzhen Stock Exchange A Share Index and Shanghai Stock Exchange A Share Index. The traders in the stock market may realize the volume change from investigating the return volatility.
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Srinivasan, V. "Supporting Novelty In Conceptual Phase Of Engineering Design." Thesis, 2010. http://etd.iisc.ernet.in/handle/2005/2266.
Full textAbstract:
Current design models, approaches and theories are highly fragmented, have seldom been compared with one another, and rarely attempted to be consolidated. Novelty is a measure of creativity of engineering products and positively influences product success. Using physical laws and effects for designing can improve the chances of creativity but they cannot be used directly owing to their inadequate current representations. It is important to address activities, outcomes, requirements and solutions in designing. Conceptual design is an early phase in engineering design and needs to be supported better. A systematic approach for designing often increases effectiveness and efficiency. Thus, the broad objective of this thesis is to develop and validate a comprehensive understanding of how designing occurs during the conceptual phase of engineering design, and to support variety and novelty of designs during this phase. The approach followed is: (a) formulate and validate an understanding of novelty and its relationships to the designing constructs, in current designing, and(b)develop and validate a support, founded on the current designing, to improve novelty. The understanding and the support are addressed, respectively, through an integrated model and a systematic framework for designing; the model and the framework comprise activities, outcomes(including laws and effects), requirements and solutions.
An integrated model of designing, GEMS of SAPPhIRE as req-sol is developed by combining activities(Generate, Evaluate, Modify, Select– GEMS), outcomes (State change, Action, Parts, Phenomenon, Input, oRgans, Effect–SAPPhIRE), requirements (req) and solutions (sol), identified from a comprehensive survey of existing design models and approaches. Validation of SAPPhIRE model with existing systems indicates that the model can be used to describe analysis and synthesis, both of which together constitute designing. Validation of the integrated model using existing videos of design sessions, to check if all its constructs are naturally used in designing, reveals that:(a) all the constructs are naturally used;(b) not all the outcomes are explored with equal intensity;(c) while high numbers of action and parts are observed, only low numbers of phenomenon, effects and organs are found. Empirical study using another set of design sessions to study the relationships between novelty and the outcomes reveals that novelty of a concept space depends on the variety of the concept space, which in turn depends on the variety of the idea space explored. Novelty and variety of a concept space also depend on the number of outcomes explored at each abstraction level. Thus, phenomena and effects are also vital for variety and novelty.
Based on the above, GEMS of SAPPhIRE as req-sol framework for designing is proposed. The framework is divided into: Requirements Exploration Stage(RES) and Solutions Exploration Stage(SES). In RES and SES, requirements and solutions respectively at all the abstraction levels including SAPPhIRE are generated, evaluated, modified and selected. The framework supports task clarification, conceptual and early embodiment phases of designing, and provides process knowledge. Comparison of the framework against existing design models, theories and approaches reveals that:(a) not all existing models, theories and approaches address activities, outcomes, requirements and solutions together;(b) those that address all these constructs together do not make a distinction between requirements and solutions; and(c) no model or approach explicitly addresses novelty. The usability of the framework and Idea-inspire is assessed by applying them in an industrial project for designing novel concepts of lunar vehicle mobility system. The use of this combined support enables identification of critical requirements, development of a large variety of ideas and concepts. One of these concepts is physically and virtually modelled, and tested, and is found to satisfy all the requirements. A catalogue of physical laws and effects is developed using SAPPhIRE model to provide assistance to designers, especially for phenomena, effects and organs. Observations found during this development are reported. A comparative validation of the framework and the catalogue for their support to design for variety and novelty is done using comparative observational studies. Results from the observational studies reveal that the variety and the novelty of concept space improve with the use of the framework, or with the frame work and the catalogue, as compared to variety and novelty with no support.