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Sato, João Ricardo. "Modelo autoregressivo vetorial com coeficientes variantes no tempo e aplicações em RMf." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-22042013-151911/.
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Os avanços nas técnicas de neuroimagem, principalmente com o de- senvolvimento da ressonância magnética funcional (RMf), vem possibilitando um melhor compreendimento dos processos e mecanismos cerebrais. Este trabalho tem como objetivo o desenvolvimento de um modelo de conectividade dinâmico entre diversas áreas cerebrais útilzando dados de RMf. A modelagem dinâmica do fluxo de informação é realizada com a estimação dos parâmetros de um modelo autoregressivo multivariado com coeficientes variandos no tempo, baseado na projeçã o de funções em bases de ondaletas. Dessa forma, um método para estimação e a derivação de suas propriedades assintóticas são apresentados. Diversos conjuntos de simulações computacionais são realizados visando a avaliação do desempenho do método proposto. Por fim, são apresentadas aplicações do modelo de conectividade variante no tempo em dados de ressonância magnética funcional.Advances in neuroimage technologies, mainly with the development of functional magnetic resonance imaging (fMRI), improve the comprehension of brain processes and mechanisms. The main goal of this work is the development of a time-varying connectivity model between many brain areas using fMRI datasets. The dynamic modelling of the information flow is related to the parameters estimation of a time-varying multivariate autoregressive process, based on functions projection in wavelet basis. We propose an estimation procedure and present its asymptotic properties. Computational simulations were performed focusing the evaluation of the proposed approach. Further, applications of these methodologies to real functional magnetic resonance datasets are presented.
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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.
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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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Gudmundsson, Gudmundur Stefan. "Essays in network modelling." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/663096.
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This thesis consists of two chapters on time series modelling. The first chapter introduces a class of vector autoregressive (VAR) models with a community structure for large panels of time series. In the model, the series are parti-tioned into latent groups such that spillovers are stronger within groups than between them. We then propose an algorithm that uses the eigenvectors of a function of the estimated autoregressive matrices to recover the communities. We study the properties of the procedure and establish its consistency. The algorithm motivates us to suggest a regularised VAR estimator, which per-forms favourably relative to a number of alternatives in a forecasting exercise. The methodology is applied to study clustering in industrial production for a set of major economies. The second chapter introduces a class of partial correlation network models with a community structure. The series form unknown groups, where correlation is higher within groups than otherwise. We propose an algorithm that consistently detects the communities using the eigenvectors of the sample covariance matrix. The procedure is used to analyse real activity clustering in the U.S. and Europe.Aquesta tesi consisteix en dos capítols sobre models de dades de sèries temporals. El primer capítol introdueix una classe de models de vector autoregressius (VAR) amb una estructura de comunitat per panels de dades de sèries temporals. En el model, les sèries es parteixen en grups latents de tal manera que els spillover són ées forts dins de grups que entre ells. Llavors proposem un algoritme que utilitza el vector d’eigen d’una funció de les matrius autoregressives estimades per recuperar les comunitats. Estudiem les propietats del procediment i establim la seva consistència. L’algoritme ens motiva a suggerir un estimador regulat del VAR, el qual actua favorablement en relació a un nombre d’alternatives en una exercici d’ estimació. La metodologia s’aplica per estudiar el clustering en la producció industrial per un conjunt d’economies importants. El segon capítol introdueix una classe de models de xarxa de correlació parcials amb una estructura de comunitat. La èerie forma grups desconeguts, on la correlació és més alta dins de grups que altrament. Proposem un algoritme que detecta consistentment les comunitats que utilitzen els vectors d’eigen de la matriu de mostra de covariáncia. El procediment s’utilitza per analitzar el clustering en l’activitat real en els EUA i Europa.
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Oliveira, Jorge Manuel Caetano de. "Significado do 1º pilar da política monetária do Eurosistema." Master's thesis, Instituto Superior de Economia e Gestão, 2002. http://hdl.handle.net/10400.5/3582.
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Mestrado em Economia Monetária e FinanceiraO presente estudo tem como objectivo fundamental investigar qual o significado do papel atribuído pelo Banco Central Europeu (BCE) ao agregado monetário largo M3 na condução da política monetária na zona euro. Partindo de um breve enquadramento teórico quanto ao papel atribuído pelo BCE à moeda, procede-se a uma análise empírica, baseada em vectores autoregressivos (usando essencialmente as variáveis macroeconómicas: taxa de crescimento do M3, hiato do M3 em termos reais, taxa de inflação e hiato do produto), no sentido de detectar evidência empírica de suporte ao papel proeminente que foi atribuído à moeda pelo BCE. As principais conclusões deste estudo apontam para a existência de uma enorme sensibilidade em torno da definição da taxa de inflação. No entanto, partindo-se da taxa de inflação medida pelo deflator do Produto Interno Bruto (PIB), a evidência empírica parece sugerir uma certa primazia como indicador de evolução futura dos preços o hiato do M3 em termos reais quando comparado quer com a taxa de crescimento do agregado monetário largo M3 quer com o hiato do produto.
The main target of this study is to investigate the meaning of the role assigned by the European Central Bank (ECB) to the broad monetary aggregate M3 in its conduction of the monetary policy for the euro area. The work begins with a brief theoretic framing of the role assigned to the money by ECB, which is followed by an empirical analysis, based on autoregressive vectors (employing essentially the following macroeconomic variables: growth rate of M3, real gap of M3, inflation rate and output gap), with the objective of detecting empirical evidence that support the prominent role of money assigned by the ECB. The main conclusions of this study support the existence of a high sensibility to the definition of the inflation rate. However, starting with the best measure of inflation rate based on Gross Domestic Product (GDP) deflator, the empirical evidence supports a certain primacy, as future inflation indicator, to the real gap of M3 rather than to the growth rate of M3 or output gap.
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Barão, Ricardo. "The relationships of alternative energies with the technology sector and non-renewable energies." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/14152.
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Este trabalho tem como objectivo compreender de que forma os investidores veem as energias renováveis: se as veem como parte do sector tecnológico, à espera de novos desenvolvimentos, ou como uma alternativa aos métodos existentes de produção de energia. Para responder a esta questão, foi desenvolvido um modelo de vectores autoregressivos com quatro variáveis de forma a se poder aplicar um Granger causality test e Impulse Response function. Os resultados sugerem que para o período de 2002-2007 à escala global ambas as hipóteses se confirmam, porém de 2009-2014 os resultados sugerem que os investidores não reconhecem as energias renováveis como um ramo do sector tecnológico, neste período. Para além disso, durante o período de 2009-2014, e quando comparados investidores Americanos com Europeus, os resultados sugerem que apenas o último identifica as energias renováveis como uma fonte viável para a produção energética.
This work aimed to understand the investor perception on clean energy: if it is seen as part of the technology sector, awaiting new developments, or as an alternative to the existing energy production methods. To answer this question, a four variable vector autoregression model was developed so that a Granger causality test and Impulse response function could be applied. The results suggest that while both hypotheses were confirmed worldwide for the period 2002-2007, from 2009 to 2014 results suggest that investors do not recognize the field of clean energy as part of the technology sector. Moreover, during the period that ranges from 2009 to 2014, and when comparing the American investor with the European investor, only the latter identifies renewable energy as a viable source of energy production.
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Mendes, Giovanna Miranda. "Efeitos dos ganhos de produtividade total dos fatores da agropecuária sobre os preços agrícolas no Brasil: 1970-2006." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11132/tde-17112015-084759/.
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A agropecuária brasileira tem crescido nas últimas décadas e os ganhos de produtividade tem sido importante neste bom desempenho do setor. O presente trabalho tem dois objetivos principais. O primeiro deles foi mensurar o crescimento desta produtividade total dos fatores na agropecuária brasileira estadual, decompondo o crescimento da PTF em progresso tecnológico e eficiência técnica. O segundo objetivo foi analisar o efeito do crescimento da PTF da agropecuária brasileira sobre os preços agrícolas, no Brasil, de 1970 a 2006. O crescimento desta produtividade foi mensurado a partir dos insumos terra, trabalho e capital na função de produção translog sob orientação do produto, a partir do método de Fronteira Estocástica de Produção e do índice de produtividade de Malmquist. Para avaliar o efeito do crescimento da PTF sobre os preços agrícolas foi construído o índice de preços agrícolas utilizando-se o Índice de preços de Laspeyres para estimar o vetor autoregressivo em painel (panel- VAR), acrescentando as variáveis produtividade total dos fatores (PTF), salário rural, financiamento agrícola e renda per capita domiciliar. Além disso, foi aplicado o teste de causalidade, no sentido de Granger, e estimada a função impulso resposta. A base de dados utilizada foi, obtida do Censo Agropecuário, a nível estadual, para os anos de 1970, 1975, 1980, 1985, 1995 e 2006. Os resultados indicaram que a taxa de crescimento da PTF foi crescente no Brasil e nos estados, sendo que, na maior parte das vezes, é explicada pelo progresso tecnológico, positivo e crescente para todos os estados. A eficiência técnica variou ao longo dos anos, apresentado taxas de crescimento médias positivas para a maioria dos estados. Em média, os estados estiveram situados abaixo da fronteira de produção da agropecuária brasileira. São Paulo foi o estado com maior nível de eficiência técnica. Embora a taxa de crescimento médio anual tenha sido positiva ao longo do período analisado, a eficiência reduziu para todos os estados analisados em 2006. Da análise dos efeitos do crescimento da PTF sobre os preços agrícolas, a PTF tem causalidade, no sentido de Granger, sobre os preços agrícolas. Na função impulso resposta, o choque inicial na variável PTF reduziu os preços nos primeiros anos. Assim, o crescimento da PTF do setor agropecuário contribuiu para o aumento da oferta de produtos, reduzindo os preços agrícolas. A maior disponibilidade de alimentos e, com a redução dos preços dos alimentos, os consumidores, principalmente os de renda mais baixa puderam ter maior acesso aos alimentos.The Brazilian agriculture has grown in recent decades and productivity gains have been important in this good performance of the sector. This work had two main objectives. The first one was measure the growth of this total factor productivity in agriculture by the Brazilian\'s states, decomposing TFP growth by technological progress, technical efficiency and economies of scale. The second objective was to analyze the effect of TFP growth of Brazilian agriculture on agricultural prices. The growth in productivity was measured from the inputs like labor, gross and capital in the translog production function, from the Stochastic Frontier Analysis and of the outputoriented Malmquist productivity index. To analyze the effect of TFP growth on agricultural prices was constructed an index of agricultural prices through the Laspeyres price index to estimate the vector autoregressive panel (panel-VAR) and establish the relationships between TFP, rural wages, agricultural finance and income per capita household. The Granger causality test and the impulse response function were used to the data panel. The database used obtained from the Agricultural Census, at the state level for the years 1970, 1975, 1980, 1985, 1995 and 2006. The results showed that the growth rate of TFP has been growing in Brazil and in the states, and technological progress explained most of the growth being positive and growing for all states. Technical efficiency varied over the years, presented positive average growth rates for most states. The states were located below the production frontier of Brazilian agriculture and São Paulo was the state with the highest level of technical efficiency. Although the average annual growth rate has been increasing over the period analyzed, the efficiency decreased to all state analyzed in 2006. The results also showed that TFP growth has causality in the sense of Granger, on agricultural prices. In the impulse response function, the initial shock in TFP decreased prices in the early years. Thus, TFP growth of the agricultural sector contributed to the increased supply of agricultural products, reducing agricultural prices. The greater availability of food and with reducing food prices, consumers, especially those from lower income might had greater access to food.
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Ooms, M. "Empirical vector autoregressive modeling." [S.l. : Rotterdam : s.n.] ; Erasmus University [Host], 1993. http://hdl.handle.net/1765/14163.
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Fidalgo, Cristina Patrícia Gouveia Dias. "Teoria generalizada da paridade do poder de compra : uma aplicação às economias da Europa Central." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/21111.
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Mestrado em Econometria Aplicada e PrevisãoNo presente estudo pretende-se analisar se os três países da Europa Central em vias de aderir à União Económica Monetária - Hungria, Polónia e República Checa - constituem, de facto, uma Zona Monetária Ótima no espírito de Mundell (1961) com os países da Zona Euro vis-à-vis a economia da Alemanha, colocando, assim, um fim à fase de transição dos últimos 16 anos. Para tal, recorre-se à teoria Generalizada da Paridade do Poder de Compra, inicialmente proposta por Enders e Hurn (1994), empiricamente testável com recurso ao modelo vetorial de correção de erros. Os resultados empíricos indicam que, para o período entre 1993 e 2019, apesar da não estacionaridade das séries (do logaritmo) da taxa de câmbio real bilateral de cada economia, existe, efetivamente, um co-movimento entre as diferentes taxas em trajetória de equilíbrio, refletindo o processo de convergência real consistente com o critério de Zona Monetária Ótima.
The present study aims to analyze whether the three Central European countries that are about to join the Economic Monetary Union - Hungary, Poland and the Czech Republic - constitute, indeed, an Optimum Currency Area in the spirit of Mundell (1961) with the countries of the Eurozone vis-à-vis the German economy, thus putting an end to the transition phase of the past 16 years. The theoretical framework is based on Generalized Theory of Purchasing Power Parity, an hypothesis initially proposed by Enders and Hurn (1994), empirically testable using the vector error correction model. The empirical results indicate that, for the period between 1993 and 2019, despite the non-stationarity of the series (of the logarithm) of the bilateral real exchange rate of each economy, there is, effectively, a co-movement between the different rates on an equilibrium path, reflecting the process of real convergence consistent with the Optimum Currency Area criterion.
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Polito, Vito. "Vector autoregressive analysis of macroeconomic policy." Thesis, University of York, 2007. http://etheses.whiterose.ac.uk/11068/.
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Brüggemann, Ralf. "Model reduction methods for vector autoregressive processes /." Berlin [u.a.] : Springer, 2004. http://www.loc.gov/catdir/enhancements/fy0818/2003067373-d.html.
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Sugita, Katsuhiro. "Bayesian analysis of cointegrated vector autoregressive models." Thesis, University of Warwick, 2004. http://wrap.warwick.ac.uk/66201/.
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This thesis concerns econometric time series modelling of cointegrated multivariate systems using a Bayesian approach. The Bayesian approach has become increasingly attractive among researchers in the fields such as biology, though still only a relatively few econometricians use these techniques. Rather than theoretical aspects of Bayesian statistics or computational techniques, we illustrate how the Bayesian methods can be useful in analysing non-linear cointegration models. In the last ten years, non-linear time series models, such as regime switching models, have become popular among applied econometricians to analyse the business cycles, policy evaluation in specific macroeconomic issues and forecasting. Cointegration analysis has been influenced by the non-linearity so that cointegration models that allow regime switching or structural breaks have been analysed by many econometricians. Unfortunately, these nonlinear cointegration models tend to be complicated both in terms of estimation and testing. We consider in this thesis a Bayesian approach to (i) a linear cointegration model, (ii) a cointegration model with Markov regime switching, and (iii) a cointegration model with multiple structural breaks, and show how easily we can analyse these models without any substantial modification. Chapter 2 proposes a simple method for detecting cointegration rank using the Bayese factors, computed by the harmonic mean of the likelihood or Schwarz' Bayesian information criterion. Then we perform Monte Carlo simulations to compare three Bayesian methods (Phillips posterior information criterion, Kleibergen and Paap method, and one proposed method) for the cointegration rank. Provided we have enough large sample size, the Phillips' posterior information criterion gives consistent results, while the results by Kleibergen and Paap method depends on the prior hyperparameters that we specify. In Chapter 3, we develop the cointegration model that allows cointegration relationships to be switched on and off depending on the regime. Unlike the classical method that requires a two-step estimation, the Bayesian method provide a straightforward estimation and testing procedure. In Chapter 4, we consider cointegration model with multiple structural breaks in the level, trend and error covariance. The more general model with breaks in both the adjustment term and the cointegrating vectors are also presented. To date, there is no research that deals with a cointegration model with unknown multiple structural breaks in any subset of the parameters.
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Feldkircher, Martin, and Florian Huber. "Adaptive Shrinkage in Bayesian Vector Autoregressive Models." WU Vienna University of Economics and Business, 2016. http://epub.wu.ac.at/4933/1/wp221.pdf.
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Vector autoregressive (VAR) models are frequently used for forecasting and impulse response analysis. For both applications, shrinkage priors can help improving inference. In this paper we derive the shrinkage prior of Griffin et al. (2010) for the VAR case and its relevant conditional posterior distributions. This
framework imposes a set of normally distributed priors on the autoregressive coefficients and the covariances of the VAR along with Gamma priors on a set of local and global prior scaling parameters. This prior setup is then generalized by introducing another layer of shrinkage with scaling parameters that push certain regions of the parameter space to zero. A simulation exercise shows that the proposed framework yields more precise estimates of the model parameters and impulse response functions. In addition, a forecasting exercise applied to US data shows that the proposed prior outperforms other specifications in terms of point and density predictions. (authors' abstract)Series: Department of Economics Working Paper Series
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Brännström, Tomas. "Bias approximation and reduction in vector autoregressive models /." Stockholm : Economic Research Institute, Stockholm School of Economics [Ekonomiska forskningsinstitutet vid Handelshögsk.] (EFI), 1995. http://www.hhs.se/efi/summary/405.
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Brännström, Tomas. "Bias approximation and reduction in vector autoregressive models." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 1995. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-878.
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In the last few decades, vector autoregressive (VAR) models have gained tremendous popularity as an all-purpose tool in econometrics and other disciplines. Some of their most prominent uses are for forecasting, causality tests, tests of economic theories, hypothesis-seeking, data characterisation, innovation accounting, policy analysis, and cointegration analysis. Their popularity appears to be attributable to their flexibility relative to other models rather than to their virtues per se. In addition, analysts often use VAR models as benchmark models. VAR modeling has not gone uncriticised, though. A list of relevant arguments against VAR modelling can be found in Section 2.3 of this thesis. There is one additional problem which is rarely mentioned though, namely the often heavily biased estimates in VAR models. Although methods to reduce this bias have been available for quite some time, it has probably not been done before, at least not in any systematic way. The present thesis attempts to systematically examine the performance of bias-reduced VAR estimates, using two existing and one newly derived approximation to the bias. The thesis is orginanised as follows. After a short introductory chapter, a brief history of VAR modelling can be found in Chapter 2 together with a review of different representations and a compilation of criticisms against VAR models. Chapter 3 reports the results of very extensive Monte Carlo experiments serving dual purposes: Firstly, the simulations will reveal whether or not bias really poses a serious problem, because if it turns out that biases appear only by exception or are mainly insignificant, there would be little need to reduce the bias. Secondly, the same data as in Chapter 3 will be used in Chapter 4 to evaluate the bias approximations, allowing for direct comparison between bias-reduced and original estimates. Though Monte Carlo methods have been (rightfully) criticised for being too specific to allow for any generalisation, there seems to be no good alternative to analyse small-sample properties of complicated estimators such as these. Chapter 4 is in a sense the core of the thesis, containing evaluations of three bias approximations. The performance of the bias approximations is evaluated chiefly using single regression equations and 3D surfaces. The only truly new research result in this thesis can also be found in Chapter 4; a second-order approximation to the bias of the parameter matrix in a VAR(p) model. Its performance is compared with the performance of two existing first-order approximations, and all three are used to construct bias-reduced estimators, which are then evaluated. Chapter 5 holds an application of US money supply and inflation in order to find out whether the results in Chapter 4 can have any real impacts. Unfortunately though, bias reduction appears not to make any difference in this particular case. Chapter 6 concludes.Diss. Stockholm : Handelshögsk.
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SANTOS, ALEXANDRE JOSE DOS. "TREE-STRUCTURE SMOOTH TRANSITION VECTOR AUTOREGRESSIVE MODELS – STVAR-TREE." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=15888@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOREsta dissertação tem como objetivo principal introduzir uma formulação de modelo não-linear multivariado, a qual combina o modelo STVAR (Smooth Transition Vector Autoregressive) com a metodologia CART (Classification and Regression Tree) a fim de utilizá-lo para geração de cenários e de previsões. O modelo resultante é um Modelo Vetorial Auto-Regressivo com Transição Suave Estruturado por Árvores, denominado STVAR-Tree e tem como base o conceito de múltiplos regimes, definidos por árvore binária. A especificação do modelo é feita através do teste LM. Desta forma, o crescimento da árvore é condicionado à existência de não-linearidade nas séries, que aponta a divisão do nó e a variável de transição correspondente. Em cada divisão, são estimados os parâmetros lineares, por Mínimos Quadrados Multivariados, e os parâmetros não-lineares, por Mínimos Quadrados Não-Lineares. Como forma de avaliação do modelo STVARTree, foram realizados diversos experimentos de Monte Carlo com o objetivo de constatar a funcionalidade tanto do teste LM quanto da estimação do modelo. Bons resultados foram obtidos para amostras médias e grandes. Além dos experimentos, o modelo STVAR-Tree foi aplicado às séries brasileiras de Vazão de Rios e Preço Spot de energia elétrica. No primeiro estudo, o modelo foi comparado estatisticamente com o Periodic Autoregressive (PAR) e apresentou um desempenho muito superior ao concorrente. No segundo caso, a comparação foi com a modelagem Neuro-Fuzzy e ganhou em uma das quatro séries. Somando os resultados dos experimentos e das duas aplicações conclui-se que o modelo STVAR-Tree pode ser utilizado na solução de problemas reais, apresentando bom desempenho.
The main goal of the dissertation is to introduce a nonlinear multivariate model, which combines the model STVAR (Smooth Transition Vector Autoregressive) with the CART (Classification and Regression Tree) method and use it for generating scenarios and forecasting. The resulting model is a Tree- Structured Vector Autoregressive model with Smooth Transition, called STVARTree, which is based on the concept of multiple regimes, defined by binary tree. The model specification is based on Lagrange Multiplier tests. Thus, the growth of the tree is conditioned on the existence of nonlinearity in the time series, which indicates the node to be split and the corresponding transition variable. In each division, linear parameters are estimated by Multivariate Least Squares, and nonlinear parameters by Non-Linear Least Squares. As a way of checking the STVAR-Tree model, several Monte Carlo experiments were performed in order to see the functionality of both the LM test and the model estimation. Best results were obtained with medium and large samples. Besides, the STVAR-Tree model was applied to Brazilian time series of Rivers Flow and electricity spot price. In the first study, the model was statistically compared to the Periodic Autoregressive (PAR) model and had a much higher performance than the competitor. In the second case, the model comparison was with Neural-Fuzzy Modeling and the STVAR-Tree model won in one of the four series. Adding both the experiments and the two applications results we conclude that the STVARTree model may be applied to solve real problems, having good results.
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Crespo, Cuaresma Jesus, Martin Feldkircher, and Florian Huber. "Forecasting with Global Vector Autoregressive Models: A Bayesian Approach." Wiley, 2016. http://dx.doi.org/10.1002/jae.2504.
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This paper develops a Bayesian variant of global vector autoregressive (B-GVAR) models to forecast an international set of macroeconomic and financial variables. We propose a set of hierarchical priors and compare the predictive performance of B-GVAR models in terms of point and density forecasts for one-quarter-ahead and four-quarter-ahead forecast horizons. We find that forecasts can be improved by employing a global framework and hierarchical priors which induce country-specific degrees of shrinkage on the coefficients of the GVAR model. Forecasts from various B-GVAR specifications tend to outperform forecasts from a naive univariate model, a global model without shrinkage on the parameters and country-specific vector autoregressions
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Dutta, Bordoloi Suwodi. "Interdependence of US Industry Sectors Using Vector Autoregression." Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-theses/1073.
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"In this study, we explore the interdependence among different US industries by examining their correlations of the stock portfolios. Furthermore, we focus on the dynamics of their interdependent relations during peaceful and volatile periods; as such relations may change due to different sensitivities of each industry to the macroeconomic conditions. More specifically, we apply Vector Autoregression (VAR) methodology on the US industry portfolios and we use variance decomposition and generalized impulse response functions to identify the strength of the impact of each industry on the others. Based on different portfolio returns of the US industries during 1962 to 2008, we find if the pattern of the dynamic relations of the industries change in different periods. We also deduce the most influential and sensitive sectors in the US domestic market. In addition, we find the direction, strength and durability of the shocks using generalized impulse response function (GIRF)."
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Schnücker, Annika [Verfasser]. "Model Selection Methods for Panel Vector Autoregressive Models / Annika Schnücker." Berlin : Freie Universität Berlin, 2018. http://d-nb.info/1176708147/34.
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Rudoy, Melanie Beth. "Multistage mean-variance portfolio selection in cointegrated vector autoregressive systems." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/46794.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 187-190).
The problem of portfolio choice is an example of sequential decision making under uncertainty. Investors must consider their attitudes towards risk and reward in face of an unknown future, in order to make complex financial choices. Often, mathematical models of investor preferences and asset return dynamics aid in this process, resulting in a wide range of portfolio choice paradigms, one of which is considered in this thesis. Specifically, it is assumed that the investor operates so as to maximize his expected terminal wealth, subject to a risk (variance) constraint, in what is known as mean-variance optimal (MVO) portfolio selection, and that the log-prices of the assets evolve according a simple linear system known as a cointegrated vector autoregressive (VAR) process. While MVO portfolio choice remains the most popular formulation for single-stage asset allocation problems in both academia and industry, computational difficulties traditionally limit its use in a dynamic, multistage setting. Cointegration models are popular among industry practitioners as they encode the belief that the log-prices of many groups of assets are not WSS, yet move together in a coordinated fashion. Such systems exhibit temporary states of disequilibrium or relative asset mis-pricings that can be exploited for profit. Here, a set of multiperiod trading strategies are developed and studied. Both static and dynamic frameworks are considered, in which rebalancing is prohibited or allowed, respectively. Throughout this work, the relationship between the resulting portfolio weight vectors and the geometry of a cointegrated VAR process is demonstrated. In the static case, the performance of the MVO solution is analyzed in terms of the use of leverage, the correlation structure of the inter-stage portfolio returns, and the investment time horizon.
(cont.) In the dynamic setting, the use of inter-temporal hedging enables the investor to further exploit the negative correlation among the inter-stage returns. However, the stochastic parameters of the per-stage asset return distributions prohibit the development of a closed-form solution to the dynamic MVO problem, necessitating the use of Monte Carlo methods. To address the computational limitations of this numerical approximation, a set of four approximate dynamic schemes are considered. Each relaxation is suboptimal, yet admits a tractable solution. The relative performance of these strategies, demonstrated through simulations involving synthetic and real data, depends again on the investment time horizon, the use of leverage and the statistical properties of the inter-stage portfolio returns.
by Melanie Beth Rudoy.
Ph.D.
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Camehl, Annika [Verfasser]. "Model Selection Methods for Panel Vector Autoregressive Models / Annika Schnücker." Berlin : Freie Universität Berlin, 2018. http://d-nb.info/1176708147/34.
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Jeon, Kyung-Seong. "An examination of stock market properties : vector autoregression approach /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9841304.
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Braun, Robin [Verfasser]. "Three Essays on Identification in Structural Vector Autoregressive Models / Robin Braun." Konstanz : KOPS Universität Konstanz, 2019. http://d-nb.info/1191693473/34.
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Netzén, Örn Marcel. "Governance and Economic Growth : - A Vector Autoregressive approach on the Frontiermarket." Thesis, Umeå universitet, Nationalekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-144502.
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Economic growth is a hot topic among economists around the world. The last century many parts of the world have faced an acceleration in the economic growth. However, that is not the case for all countries and today there is a large economic gap between the rich and poor countries. But why have some parts of the world succeeded to create economic growth while others do not? The purpose of this study is to create a deeper understanding of the mechanism between economic growth and governance in the frontier market. To do this, a Vector autoregressive time series model will be used. The frontier market is an ad-hoc market index containing 22 countries that have not been classified as developing countries yet. In the poor parts of the world high level corruption and lack of political stability such as rule of law is a fact. Hence, the study will use control of corruption, rule of law as governance variables to investigate the association between governance and economic growth among the countries in the frontier market. Further it will investigate if there is a Granger causality between governance and economic growth and whether it is running from economic growth to governance or conversely. The results implies that there is association between governance and economic growth for Bahrain, Bangladesh, Croatia, Kazakhstan, Lebanon, Lithuania, Mauritius, Morocco, Pakistan, Romania, Slovenia, Serbia, Sri Lanka and Vietnam. But, the question remains if it is good governance that creates economic growth or if it is economic growth that creates good governance in the frontier market
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Sjödin, Wågberg Anton. "Prices on electricity and the prices on stocks : -A Vector autoregressive approach." Thesis, Umeå universitet, Nationalekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-153448.
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This study will investigate if a relationship exists between the price of electricity and the Swedish stock market. This study will also try to investigate what consequences an increase in the price of electricity will have on the return of the Swedish stock market. Economic theory and earlier literature will then be used to try to explain the results obtained in this study. The results from the tests performed in this study imply that a one-way Granger-causality exists between the prices on electricity and the price on the OMX 30. The impulse response functions performed shows that a positive shock in the price on electricity will predict an increase in the return of the OMX 30 in the short run. This effect may come from the existence of a countercyclical risk premium. Although further research needs to be performed to conclude that this is the true reason for the observed result.
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Cao, Z. "Modelling economic interdependencies of international tourism demand : the global vector autoregressive approach." Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/810483/.
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Tourism demand is one of the major areas of tourism economics research. The current research studies the interdependencies of international tourism demand across 24 major countries around the world. To this end, it proposes to develop a tourism demand model using an innovative approach, called the global vector autoregressive (GVAR) model. While existing tourism demand models are successful in measuring the causal effects of economic variables on tourism demand for a single origin-destination pair, they tend to miss the spillover effects onto other countries. In the era of globalisation, tourism destinations become interdependent on each other. Impacts of a distant event can be transmitted across borders and be felt globally. Hence, modelling international tourism demand requires one to go beyond a particular origin-destination pair, and take into account the interdependencies across multiple countries. The proposed approach overcomes the ‘curse of dimensionality’ when modelling a large set of endogenous variables. The empirical results show that, to different extents, co-movements of international tourism demand and of macroeconomic variables are observed across all the 24 countries. In the event of a negative shock to China’s real income level and that to China’s own price level, it is found that in the short run, almost all countries will face fluctuations in their international tourism demand and their own price. But in the long run the shocks will impact on developing countries and China’s neighbouring countries more deeply than on developed countries in the West. The current research contributes to the knowledge on tourism demand. It models tourism demand in the setting of globalisation and quantifies the interdependencies across major countries. On the practical front, tourism policy makers and business practitioners can make use of the model and the results to gauge the scale of impacts of unexpected events on the international tourism demand of their native markets.
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Zhang, Wei. "A sensitivity study on identification schemes of the structural vector autoregression /." free to MU campus, to others for purchase, 2001. http://wwwlib.umi.com/cr/mo/fullcit?p3025669.
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Unosson, Måns. "A Mixed Frequency Steady-State Bayesian Vector Autoregression: Forecasting the Macroeconomy." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297406.
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This thesis suggests a Bayesian vector autoregressive (VAR) model which allows for explicit parametrization of the unconditional mean for data measured at different frequencies, without the need to aggregate data to the lowest common frequency. Using a normal prior for the steady-state and a normal-inverse Wishart prior for the dynamics and error covariance, a Gibbs sampler is proposed to sample the posterior distribution. A forecast study is performed using monthly and quarterly data for the US macroeconomy between 1964 and 2008. The proposed model is compared to a steady-state Bayesian VAR model estimated on data aggregated to quarterly frequency and a quarterly least squares VAR with standard parametrization. Forecasts are evaluated using root mean squared errors and the log-determinant of the forecast error covariance matrix. The results indicate that the inclusion of monthly data improves the accuracy of quarterly forecasts of monthly variables for horizons up to a year. For quarterly variables the one and two quarter forecasts are improved when using monthly data.
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Lim, Néhémy. "Estimation de modèles autorégressifs vectoriels à noyaux à valeur opérateur : Application à l'inférence de réseaux." Thesis, Evry-Val d'Essonne, 2015. http://www.theses.fr/2015EVRY0007/document.
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Dans l’analyse des séries temporelles multivariées, la plupart des modèles existants sont utilisés à des fins de prévision, c’est-à-dire pour estimer les valeurs futures du système étudié à partir d’un historique de valeurs observées dans le passé. Une autre tâche consiste à extraire des causalités entre les variables d’un système dynamique. C’est pour ce dernier problème à visée explicative que nous développons une série d’outils. À cette fin, nous définissons dans cette thèse une nouvelle famille de modèles autorégressifs vectoriels non paramétriques construits à partir de noyaux à valeur opérateur. En faisant l’hypothèse d’une structure sous-jacente creuse, la parcimonie du modèle est contrôlée en imposant dans la fonction de coût des contraintes de parcimonie aux paramètres du modèle (qui sont en l’occurrence des vecteurs qui pondèrent une combinaison linéaire de noyaux). Les noyaux étudiés possèdent parfois des hyperparamètres qui doivent être appris selon la nature du problème considéré. Lorsque des hypothèses de travail ou des connaissances expertes permettent de fixer les paramètres du noyau, le problème d’apprentissage se réduit à la seule estimation des paramètres du modèle. Pour optimiser la fonction de coût correspondante, nous développons un algorithme proximal. A contrario, lorsqu’aucune hypothèse relative aux variables n’est disponible, les paramètres de certains noyaux ne peuvent être fixés a priori. Il est alors nécessaire d’apprendre conjointement les paramètres du modèle et ceux du noyau. Pour cela, nous faisons appel à un schéma d’optimisation alterné qui met en jeu des méthodes proximales. Nous proposons ensuite d’extraire un estimateur de la matrice d’adjacence encodant le réseau causal sous-jacent en calculant une statistique des matrices jacobiennes instantanées. Dans le cas de la grande dimension, c’est-à-dire un nombre insuffisant de données par rapport au nombre de variables, nous mettons en oeuvre une approche d’ensemble qui partage des caractéristiques du boosting et des forêts aléatoires. Afin de démontrer l’efficacité de nos modèles, nous les appliquons à deux jeux de données : des données simulées à partir de réseaux de régulation génique et des données réelles sur le climatIn multivariate time series analysis, existing models are often used for forecasting, i.e. estimating future values of the observed system based on previously observed values. Another purpose is to find causal relationships among a set of state variables within a dynamical system. We focus on the latter and develop tools in order to address this problem. In this thesis, we define a new family of nonparametric vector autoregressive models based on operator-valued kernels. Assuming a sparse underlying structure, we control the model’s sparsity by defining a loss function that includes sparsity-inducing penalties on the model parameters (which are basis vectors within a linear combination of kernels). The selected kernels sometimes involve hyperparameters that may need to be learned depending on the nature of the problem. On the one hand, when expert knowledge or working assumptions allow presetting the parameters of the kernel, the learning problem boils down to estimating only the model parameters. To optimize the corresponding loss function, we develop a proximal algorithm. On the other hand, when no prior knowledge is available, some other kernels may exhibit unknown parameters. Consequently, this leads to the joint learning of the kernel parameters in addition to the model parameters. We thus resort to an alternate optimization scheme which involves proximal methods. Subsequently, we propose to build an estimate of the adjacency matrix coding for the underlying causal network by computing a function of the instantaneous Jacobian matrices. In a high-dimensional setting, i.e. insufficient amount of data compared to the number of variables, we design an ensemble methodology that shares features of boosting and random forests. In order to emphasize the performance of the developed models, we apply them on two tracks : simulated data from gene regulatory networks and real climate data
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Horton, Wendy Elizabeth. "A vector autoregressive model of a regional Phillips curve in the United States." Thesis, Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/30515.
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Degerli, Mecit Mert. "Fault detection of bearings based on AutoRegressive modelling and Support Vector Machine classification." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.
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Bearings are the common mechanical components and they have an authentic role generally in every kind of machines or applications. Therefore it becomes more and more important to understand properly the behaviour and the nature of the bearing and also their working conditions. For this reason, the data from the components on the machine as bearings in the modern industry; the importance of reducing machine downtime and machine costs, increasing machine performance and achieving a more stable operation is increasing day by day. For that purpose, different solutions have been provided to detect and diagnose faulty situations in bearings with different application-oriented approaches. In this study, by means of vibration based method; the vibration signals coming from the bearings are filtered by Wavelet analysis to avoid non-stationarities and then the filtered signal is modeled according to the AutoRegressive (AR) process. The coefficients of the related model is the basis for the Machine Learning algorithm Support Vector Machines (SVM) by optimizing with Bayesian Optimization to perform Fault Detection and Identification (FDI). This usage of AR process provides a useful forward-looking method for appropriate feature selection. In this study the data which was provided by Center for Intelligent Maintenance Systems is used and the results have been discussed and concluded.
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Bertsche, Dominik [Verfasser]. "Three Essays on Identification and Dimension Reduction in Vector Autoregressive Models / Dominik Bertsche." Konstanz : KOPS Universität Konstanz, 2020. http://d-nb.info/1209879778/34.
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Bwire, Thomas. "Aid, fiscal policy and macroeconomy of Uganda : a cointegrated vector autoregressive (CVAR) approach." Thesis, University of Nottingham, 2012. http://eprints.nottingham.ac.uk/12918/.
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While confronting the question of aid effectiveness, an important issue (but often ignored) in the context of a developing country like Uganda is which GDP measure would be most reliable as this is crucial for measuring the macroeconomic impact of aid. The most commonly used GDP measure in the aid-growth literature is typically from World Development Indicators (WDI) or Penn World Tables (PWT) (being considered the most reliable or the easiest to obtain). However, disparities in GDP from alternative sources are common and in practice one has different estimates of the level, change and growth of GDP for the same country over the same period. This is of a particular concern especially in developing countries (without exception) where the informal and subsistence sectors are a large share of the economy (Jerven, 2010) and where not all transactions in the formal sector are recorded (MacGaffey, 1991), and the quality of data is still very poor and measurement perceptions of macroeconomic aggregates are varied and weak (Mukherjee, White and Wuyts, 1998). Because the source chosen for GDP may affect inferences on growth and economic performance for African countries, the thesis entry point was an analysis of alternative sources of GDP, and aimed to construct a consistent GDP series for Uganda. The extent of discrepancy in GDP estimates was investigated, and the year on year percentage GDP growth rates, including percentage and average growth rate discrepancies were derived, with a particular focus on sub-periods when GDP from alternative sources diverge most. Although UBOS and WDI real UGX GDP year on year growth rate estimates had a 3.6 percentage point average absolute discrepancy per year, they are consistent, similar and cointegrated. In fact, over 1970-76 and 2000-08 the two series are very close, and they are quite close for 1978-83 and 1993-99. Therefore, either series can be considered to represent trends in the size of the macroeconomy. However, the UBOS real series is smoother and produces a more stable measure of GDP than does the WDI series and it is the underlying source from which macroeconomic data is sought by the international agencies, including WDI. Given this, the less volatile UBOS real series (real UGX GDP/U) was preferred especially as there was less need to incorporate dummies in the rest of the thesis. Fiscal data and private consumption (our preferred measure of growth) in the thesis were derived from this same source. Two dynamics relationships, i.e. one between foreign aid and domestic fiscal variables, and the other between foreign aid, domestic fiscal variables, exports and private consumption in Uganda are assessed using annual data over the period 1972 to 2008. ACVAR model is employed and executed using CATS in RATS, version 2.1and E-views 7.2. Features of the data over 1972-79, a period characterized by political and economic instability in Uganda and the effect of policy shift due to structural adjustment programme and the Museveni regime in Uganda are reflected in the analysis. Considering first the core fiscal variables, we find that aid and fiscal variables form a long-run stationary relation and the role of structural changes remain unclear as the policy shift dummy seems unimportant for the long-run fiscal relation. A test of structural links between aid and fiscal variables reveals that aid is a significant element of long-run fiscal equilibrium, and the hypothesis of aid exogeneity is not statistically supported. In the long-run, aid is associated with increased tax effort, reduced domestic borrowing and increased public spending, although aid additionality/illusion hypothesis remains inconclusive given the nature of the DAC measure of aid used here. A decomposition of the common trends shows that shocks to tax revenue are the pulling forces, while empirical shocks to domestic borrowing, government spending and aid are the pushing forces of the fiscal system. In terms of policy, it is crucial for the donors to increase the reliability and predictability of aid in order for Uganda to improve fiscal planning and reduce the need to resort to costly domestic borrowing. In addition, one way to make inference on the relationship between aid and spending more clear is for donors to coordinate aid delivery systems and also make aid more transparent. Finally, we extended the fiscal analysis and also considered how aid, mediated by the fiscal variables, and exports impact on the growth of the private sector- a relationship a kin to the growth response to aid in Uganda. Results show that aid and the Ugandan macrovariables are significantly cointegrated, and a battery of sensitivity and robust checks demonstrate that the cointegration rank is 2. These are formally identified as representing respectively the statistical analogue of the budgetary equilibrium among the core fiscal variables and the link between aid, fiscal variables, exports and growth in private consumption. Using this rank condition, the hypotheses of long-run exclusion of aid and aid exogeneity are optimally tested within a system of equations, but these are not statistically supported. With particular reference to the growth relation, we find broad support that aid has had, in the long-run, a positive impact on the private sector, albeit indirectly through public spending, and deficit financing is associated with ‘crowd in’ effect linked to public investment spending. However, the belief that ‘earmarking’ aid to investment spending contributes to achieving target growth rates may be exaggerated. It is the productivity, not the level of investment that matter. On the contrary, aid may have an important role in supporting consumption spending, and this happens to be more beneficial to growth in Uganda than may be commonly acknowledged. The role of structural changes remains unclear as the policy shift dummy seems unimportant for the long-run fiscal and growth relations, but may matter for the short-run.
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Petrov, Krassimir M. "Forecasting the dairy price complex : an application of Bayesian Vector autoregression modelling /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488193272066522.
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Lee, Joo Young, and Youn Mi Lee. "Dynamic Impact of Aging on Income Inequality in the U.S. with Vector Autoregressive Model." Digital Commons @ East Tennessee State University, 2020. https://dc.etsu.edu/secfr-conf/2020/schedule/57.
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Income inequality has been showing a steady increase for past decades and will be worsened in the future (Piketty, 2014). One of the most important factors to explain the worsening income inequality can be aging. Previous studies on aging focus on its impact on traditional issues such as health, retirement, and economic growth. This study finds the direct relationship between aging and income inequality using the vector autoregressive (VAR) model (Blanchard and Quah, 1989). The VAR model is useful to analyze the long-run response of aging on income inequality. The empirical results will verify the negative impact of aging on income inequality in the U.S. The governmental efforts to reduce the negative impact of aging on health care and pensions could delay the worsening income inequality.
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Semião, Patrícia Margarida Floro. "Efeitos macroeconómicos do investimento público central e local: uma comparação internacional." Master's thesis, ISEG, 2008. http://hdl.handle.net/10400.5/21971.
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Mestrado em Economia.O investimento público tem sido alvo de interesse por parte das investigações económicas mais recentes, enquanto uma variável que pode fomentar o crescimento económico. Através da observação dos seus impactos na economia, consegue-se compreender se os esforços empreendidos no investimento público são eventualmente produtivos. Este estudo pretende analisar essa produtividade, medindo os efeitos do investimento público no PIB, no investimento privado e no emprego, no longo prazo. A especificidade do exposto neste trabalho consiste numa desagregação diferente do investimento público, ao analisar em separado os efeitos do investimento feito pela administração central, pela administração local e pela administração estadual, quando aplicável. É efectuado para sete países da União Europeia, a saber; Alemanha, Bélgica, Finlândia, França, Holanda, Itália e Portugal, permitindo assim uma comparação a nível internacional. A abordagem metodológica baseia-se em modelos de vectores autoregressivos - modelos VAR. Com base nas funções acumuladas de resposta a um impulso por tipo de investimento público, são calculadas as elasticidades, as produtividades marginais parciais e totais do PIB e do investimento privado, bem como as taxas de rendibilidade parciais e totais do PIB. É ainda calculado o número marginal de empregos criados. Conclui-se que, de modo geral, o investimento público por subsector é produtivo, apresentando efeitos positivos no PIB, no investimento privado e no emprego. Por tipo de investimento público, o investimento local tem sempre efeitos positivos no PIB, apresenta impactos positivos no investimento privado para um maior número de países e, no emprego, embora as elasticidades de longo prazo sejam superiores, os empregos criados são menores do que para o investimento central.
Public investment has been a target of many economical investigations in the recent years, because of its potential to promote economic growth. Through the observation of its impacts in the economy, one can understand if the efforts of public investment are productive. The aim of this study is to analyse that productivity, through the measurement of the public investment effects in the long run in GDP, private investment and employment. The specificity of this work, is the different disaggregation of public investment, that analyse separately the effects of public investment made by the central administration, local administration and state administration, when exists. It is made to seven European Union countries: Germany, Belgium, Finland, France, Netheriands, Italy and Portugal, allowing an intemational comparison. The methodological approach is a model of vector autoregression - a VAR model. With theaccumulated impulse response functions for different t ypes of public investment, elasticities, partial and total marginal productivities and, partial and total rates of retum are calculated for GDP. The number of marginal jobs is also calculated. One can conclude that, generally, public investment is productive, with positive effects in GDP, in private investment and in employment. For a analyse through different types of public investment, the local one hasalways positive effects in GDP, has positive effects in private investment for most countries and, in employment, although the elasticities are greater, the job creation are less than for the central investment.
info:eu-repo/semantics/publishedVersion
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Serpeka, Rokas. "Analyzing and modelling exchange rate data using VAR framework." Thesis, KTH, Matematik (Inst.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-94180.
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Abstract In this report analysis of foreign exchange rates time series are performed. First, triangular arbitrage is detected and eliminated from data series using linear algebra tools. Then Vector Autoregressive processes are calibrated and used to replicate dynamics of exchange rates as well as to forecast time series. Finally, optimal portfolio of currencies with minimal Expected Shortfall is formed using one time period ahead forecasts
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Tutar, Eser. "Inflation Targeting in Developing Countries and Its Applicability to the Turkish Economy." Thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/34288.
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Inflation targeting is a monetary policy regime, characterized by public announcement of official target ranges or quantitative targets for price level increases and by explicit acknowledgement that low inflation is the most crucial long-run objective of the monetary authorities. There are three prerequisites for inflation targeting: 1)central bank independence,2)having a sole target,3)existence of stable and predictable relationship between monetary policy instruments and inflation.In many developing countries, the use of seigniorage revenues as an important source of financing public debts, the lack of commitment to low inflation as a primary goal by monetary authorities, considerable exchange rate flexibility, lack of substantial operational independence of the central bank or of powerful models to make domestic inflation forecasts hinder the satisfaction of these requirements. This study investigates the applicability of inflation targeting to the Turkish economy. Central bank independence in Turkey has been mainly hindered by "fiscal dominance" through monetization of high budget deficits. In addition, although serious steps have been taken recently under a new law to have an independent central bank, such as formal commitment to the achievement of price stability as the primary objective and the prohibition of credit extension to the government, the central bank does not satisfy independence criteria due to the problems associated with the appointment of the government and the share of the Treasury within the bank. Having a sole inflation target was hindered by the existence of fixed exchange rate system throughout the years. However, in February 2001, Turkey switched to a floating exchange rate regime, which is important for a successful inflation-targeting regime. Having a sole target within the system has also been supported by the new central bank law, which gives priority to price stability and supports any other objective as long as it is consistent with price stability. In this thesis, an empirical investigation has been made in order to assess the statistical readiness of Turkey to satisfy the requirements of inflation-targeting by making use of vector autoregressive (VAR) models. The results suggest that inflation is an inertial phenomenon in Turkey and money, interest rates and nominal exchange rates innovations are not economically and statistically important determinants of prices. Most of the variances in prices are explained by prices themselves. According to the VAR evidence, the direct linkages between monetary policy instruments and inflation do not seem to be strong, stable, and predictable. As a result, while the second requirement of the inflation-targeting regime seems to have been satisfied, there are still problems associated with the central bank independence and the existence of stable and predictable relationship between monetary policy instruments and inflation in Turkey.Master of Arts
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Jordanov, Jordan V. "The size anomaly in the London Stock Exchange : an empirical investigation." Thesis, Loughborough University, 1998. https://dspace.lboro.ac.uk/2134/7067.
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This study tests the size effect in the London Stock Exchange, using data for all nonfinancial listed firms from January 1985 to December 1995. The initial tests indicate that average stock returns are negatively related to firm size and that small firm portfolios earn returns in excess of the market risk. Further, the study tests whether the size effect is a proxy for variables such as the Book-to- Market Value and the Borrowing Ratio, as well as the impact of the dividend and the Bid- Ask spread on the return of the extreme size portfolios. The originality of this study is in the application of the Markov Chain Model to testing the Random Walk and Bubbles hypotheses, and the Vector Autoregression (VAR) framework for testing the relationship of macroeconomic variables with size portfolio returns.
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White, Alexander B. "Pre- and post-retirement asset allocation: a simulation of retirement investment strategies for agricultural producers." Diss., Virginia Tech, 1995. http://hdl.handle.net/10919/38097.
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This research simulates pre-retirement investment scenarios for agricultural producers. Thirty-two investment scenarios are examined, with each scenario differing with respect to retirement vehicle, investment strategy of the producer, and the use of a cash margin for reinvestment in the operation versus prepaying term debt (cash preference). The retirement vehicles included in this study are Individual Retirement Accounts (IRAs), Simplified Employee Pension Plans (SEPs), and 401(k) plans. Investment strategies reflect the producer's preference for investing in conservative, balanced, or aggressive assets, or a combination of these assets. Further, these scenarios are examined for three methods of capitalization: Case I- an operation with a 50 percent debt/asset ratio; Case II - an operation with a 65 percent debt/asset ratio; Case III - an operation with a 65 percent debt/asset ratio with a majority of the farm land being leased.
The analytical model simulates the annual cash flows of a commercial agricultural operation for each investment scenario over a 30-year period. Stochastic rates of return, generated using a vector-autoregressive (VAR) model, are incorporated into the simulation model. Each scenario is replicated 100 times using different vectors of stochastic rates of return.
Results show investment in retirement vehicles does not significant reduce ending farm assets, regardless of investment strategy or cash preference of the producer. Use of retirement vehicles does have a significant positive impact on ending net worth for the producer. IRAs are not significant investment tools for producers (or spouses) who are participants in another qualified retirement plan.
Investment strategy has a major impact on ending net worth. Aggressive and dynamic (aggressive to conservative as retirement approaches) investment strategies dominate conservative and balanced strategies. Use of cash margin to prepay debt has no advantage over reinvesting in the farm.
Retirement vehicles greatly improve the probability of meeting estimated family living needs during retirement, and generate greater diversity and liquidity of the retirement portfolio. Further, retirement vehicles are more important for producer with highly-leveraged operations and for producers who lease a majority of their assets.Ph. D.
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Sharp, Gary David. "Lag length selection for vector error correction models." Thesis, Rhodes University, 2010. http://hdl.handle.net/10962/d1002808.
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This thesis investigates the problem of model identification in a Vector Autoregressive framework. The study reviews the existing research, conducts an extensive simulation based analysis of thirteen information theoretic criterion (IC), one of which is a novel derivation. The simulation exercise considers the evaluation of seven alternative error restricted vector autoregressive models with four different lag lengths. Alternative sample sizes and parameterisations are also evaluated and compared to results in the existing literature. The results of the comparative analysis provide strong support for the efficiency based criterion of Akaike and in particular the selection capability of the novel criterion, referred to as a modified corrected Akaike information criterion, demonstrates useful finite sample properties.
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Podstawski, Maximilian [Verfasser]. "Unconventional Identification in Vector Autoregressive Models: Empirical Essays on Credit, Risk and Uncertainty / Maximilian Podstawski." Berlin : Freie Universität Berlin, 2016. http://d-nb.info/1113593113/34.
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Crespo, Cuaresma Jesus, Gernot Doppelhofer, Martin Feldkircher, and Florian Huber. "Spillovers from US monetary policy: Evidence from a time-varying parameter global vector autoregressive model." Published by John Wiley & Sons Ltd on behalf of the Royal Statistical Society, 2019. http://dx.doi.org/10.1111/rssa.12439.
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The paper develops a global vector auto-regressive model with time varying pa-
rameters and stochastic volatility to analyse whether international spillovers of US monetary
policy have changed over time. The model proposed enables us to assess whether coefficients
evolve gradually over time or are better characterized by infrequent, but large, breaks. Our find-
ings point towards pronounced changes in the international transmission of US monetary policy
throughout the sample period, especially so for the reaction of international output, equity prices
and exchange rates against the US dollar. In general, the strength of spillovers has weakened
in the aftermath of the global financial crisis. Using simple panel regressions, we link the vari-
ation in international responses to measures of trade and financial globalization. We find that
a broad trade base and a high degree of financial integration with the world economy tend to
cushion risks stemming from a foreign shock such as US tightening of monetary policy, whereas
a reduction in trade barriers and/or a liberalization of the capital account increase these risks.
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Kobler, Alexander. "Sources and dynamics of macroeconomic fluctuations in Switzerland : evidence from a structural vector autoregressive approach /." Bern ; Berlin ; Bruxelles [etc.] : P. Lang, 2000. http://aleph.unisg.ch/hsgscan/hm00001729.pdf.
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Wong, Kin-man, and 黃健文. "A vector autoregression (VAR) model of housing starts and housing price in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hdl.handle.net/10722/194603.
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It is observed that there are many different models about housing price. Yet, this is relatively smaller number of studies about housing starts. This thesis is an empirical study to work out the relationship between housing starts, housing price and other economic and policy instrumental factors. To achieve this objective, a Vector Autoregression (VAR) model is built since there is inter-relationship between housing starts and housing price.
By applying previous models filled with the research gaps, a new VAR model about the housing starts and housing price in Hong Kong is built. Four hypotheses are tested in the thesis. The first and second hypotheses are if housing starts and housing price are affected by the given exogenous variables. The third hypothesis is if the past movement of economic variables reliable in predicting future values of that variable. The last hypothesis is to test if the “high-land-price” policy really pushes up the housing price.
The empirical results found in this thesis are a little bit different to previous studies in Hong Kong and overseas. Factors which are frequently proved to be statistically significant are not significant in this study (e.g. interest rate and tender price index). Developers in Hong Kong are found to care more about the future market rather than the current market conditions. Many factors do not exert an influence directly on housing starts but indirectly through their impact to the change of the change of the housing price.
It is interesting to know that housing starts react negatively to a change in housing price. An increase in the change of housing price is a bullish signal for the developers. They will hold the land for a while until they expect the peak is coming upon the completion of a project. Therefore, the empirical results suggest the government has to introduce some policies which will lead to a fall in housing price in case that she wants to increase the supply of new private residential housing. Developers will accelerate the applications to commence construction when they expect there will be a downward trend in the housing price (which is shown by a negative change of the housing price..published_or_final_version
Real Estate and Construction
Master
Master of Philosophy
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Cheong, Onn Kee. "A Study of the Interdependence of Four Major Stock Markets Using a Vector Autoregression." Thesis, University of North Texas, 1989. https://digital.library.unt.edu/ark:/67531/metadc500682/.
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The question for this thesis is whether the four major stock markets--the United States, Great Britain, West Germany, and Japan are interdependent or segmented. The study period runs from February 1979 to June 1987, with the Wall Street Journal as a source of data. The Granger causality test is used to test for relationships among the four major stock markets. The thesis is divided into five chapters-- 1) statement of the problem; 2) survey of literature; 3) methodology; 4) results and 5) conclusions. The overall findings of this thesis indicate that there are few or no comovement similarities among all the four stock markets. However, the findings do point out the significant influence of the United States stock market on the other three stock markets.
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Afonso, Ana Catarina Leitão. "Bond fund runs: The financial crisis case." Master's thesis, NSBE - UNL, 2014. http://hdl.handle.net/10362/11686.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and EconomicsThis paper studies the monthly flows of bond fund geographically focused on Europe and on the United States in the period between 2002 and 2012, with special attention to the effect of the financial crisis of 2008. Through the usage of the panel quantile regression model, this study aims to identify which funds, in terms of their characteristics, are more likely to suffer a run. The main finding is that the impact of the characteristics of fund flows is not equal for all funds, varying with issuer entity, the state of the economy as well as the focus of the fund. During the financial crisis, runs were more pronounced, situation that still affects funds geographically focused on Europe.
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Bergqvist, Martin. "Dynamics in the rural housing markets : A Vector Autoregressive approach to the ripple effect in Sweden." Thesis, Umeå universitet, Nationalekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-124800.
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This thesis examines the “ripple effect” and its presence on a regional level within Swedish counties. This effect implies that central housing markets “lead” the fluctuations in prices, and other local markets follow with a time lag. Vector auto regressive methods are used to capture the effects of real house price changes on single-family houses during the years 1984 to 2014, within Sweden’s large and sparsely populated counties. The results confirms the presence of this effect between Stockholm and regional capitals, but cannot confirm that this effect continuous from regional capitals to their respective neighbouring municipalities. But the results indicate that there are reasons to believe that the “ripple effect” is there, but that there are some internal dynamics within some counties that this thesis cannot explain and that need further research.
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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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Gilleran, Sean. "Online Regime Switching Vector Autoregression Incorporating Spatio-temporal Aspects for Short Term Wind Power Forecasting." Thesis, KTH, Elkraftteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-217117.
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This master thesis examines short term wind power forecasting time series models focusing on regimes conditioned to meteorological conditions and the incorporation of spatio-temporal aspects. Novel regime switching autoregressive and vector autoregressive models are proposed, implemented in a .NET framework, and evaluated. The vector autoregressive framework takes advantage of cross-correlation between sites incorporating upstream online production information from all wind farms within a given region. The regimes are formed using K-means clustering based on forecast meteorological conditions. Each of the proposed models are fit to hourly historical data from all of 2015 for 24 wind farms located in Sweden and Finland. Forecasts are generated for all of 2016 and are evaluated against historical data from that year for each of the 24 wind farms. The proposed models are successfully implemented into the .NET framework of Vitec Software’s Aiolos Forecast Studio, which is widely used in the Northern and Western Europe. Vitec’s Aiolos wind power forecast model is based on an ensemble of numerical weather prediction models and adaptive statistical machine learning algorithms. The proposed models are found to have significantly lower mean absolute error and root mean squared error compared to the Aiolos model and autoregressive model benchmarks. The improved short term wind power forecast will inform operation and trading decisions and translate to significant reductions in balancing costs for Vitecs customers. The improvement is valued at as much as between 9.4 million Euros to 42.3 million Euros in reduced balancing costs. Spatio-temporal aspects for wind power forecasting is shown to continue to be promising for improving current state-of-the-art wind power forecasting.I detta arbete undersöks och implementeras autoregressiva modeller för vindkraftprognoser för en kort tidshorisont. Metoden tar hänsyn till samvariationer i tid och rum mellan olika vindkraftanläggningar och använder regimer som baseras på väderförhållanden för att förbättra prognoserna. Vi föreslår nya autoregressiva regimer, implementerar modellerna i .NET och utvärderar dem. Vektor autoregressiva modeller utnyttjar korrelationen mellan olika anläggningar genom att ta med information i närtid från andra anläggningar i samma region i modellen och på så vis förbättra prognoserna. Regimerna skapas med en klustermetod för K-medelvärde som baseras på väderförhållandena. Alla föreslagna modeller anpassas till historiska data för 2015 för 24 vindkraftanläggningar i Sverige och Finland. Prognoser skapas för 2016 och används för att utvärdera modellerna för var och en av de 24 anläggningarna. De föreslagna modellerna har implementerats i .NET i miljön för Vitecs Aiolos Forecast Studio, vilket är ett program som används av många operatörer i norra och västra Europa för att göra vindkraftprognoser. Aiolos modell baseras på en rad olika numeriska väderprognosmodeller och adaptiva statistiska maskinlärningsalgoritmer. De föreslagna modellerna visar sig ha lägre fel jämfört med Aiolos modell och andra autoregressiva modeller som använts som riktmärken. De förbättrade kortsiktiga vindkraftsprognoserna kommer vara underlag för operativa och finansiella beslut för Vitecs kunder och innebära betydande minskningar av balanskostnader. Förbättringen uppskattas kunna minska kostnaderna för Vitecs kunder med så mycket som mellan 9.4 miljoner och 42.3 miljoner Euro. Att utnyttja korrelationer mellan olika vindkraftanläggningar visar sig ha fortsatt stor betydelse för att förbättra vindkraftprognoser.
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Barassi, Marco Raffaele. "Identifying causal structures of cointegrated vector autoregression with an application to the G7 interest rates." Thesis, Imperial College London, 2001. http://hdl.handle.net/10044/1/8719.
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