Exponential smoothing algorithms are very attractive for the practical world such as in industry. When considering bivariate exponential smoothing methods, in addition to the properties of univariate methods, additional properties give insight to relationships between the two components of a process, and also to the overall structure of the model. It is important to study these properties, but even with the merits the bivariate exponential smoothing algorithms have, exponential smoothing algorithms are nonstatistical/nonstochastic and to study the properties within exponential smoothing may be worthless. As an alternative approach, the (bivariate) ARIMA and the structural models which are classes of statistical models, are shown to generalize the exponential smoothing algorithms. We study these properties within these classes as they will have implications on exponential smoothing algorithms. Forecast properties are studied using the state space model and the Kalman filter. Comparison of ARIMA and structural model completes the study. / Mathematical Sciences / M. Sc. (Statistics)

This study provides evidence of the relationship between bank-granted credit and business cycles in South Africa. The study is conducted in three phases, namely qualitative research (Phase I), quantitative research (Phase II) and econometric analysis (Phase III). A sequential (connected data) mixed methodology (Phase I and II) is used to collect and analyze primary data from market participants. The qualitative research (Phase I) involves structured interviews with influential or well informed people on the subject matter. Phase I of the study is used to understand the key determinants of bank credit in South Africa and to appreciate how each of the credit aggregates behaves during alternate business cycles. Qualitative survey results suggest key determinants of commercial bank credit in South Africa as economic growth, collateral value, bank competition, money supply, deposit liabilities, capital requirements, bank lending rates and inflation. The qualitative results are used to formulate questions of the structured survey questionnaire (Quantitative research- Phase II). The ANOVA and Pearman’s product correlation analysis techniques are used to assess relationship between variables. The quantitative results show that there is direct and positive relationship between bank lending behavior and credit aggregates namely economic growth, collateral value, bank competition and money supply. On the other hand, the results show that there is a negative relationship between credit growth and bank capital and lending rates. Overall, the quantitative findings show that bank lending in South Africa is procyclical. The survey results indicate that the case for demand-following hypothesis is stronger than supply-leading hypothesis in South Africa. The econometric methodology is used to augment results of the survey study. Phase III of the study re-examines econometric relationship between bank lending and business cycles. The study employs cointegration and vector error correction model (VECM) techniques in order to test for existence of long-run relationship between the selected variables. Granger causality test technique is applied to the variables of interest to test for direction of causation between variables. The study uses quarterly data for the period of 1980:Q1 to 2013:Q4. Business cycles are determined and measured by Gross Domestic Product at market prices while bank-granted credit is proxied by credit extension to the private sector. The econometric test results show that there is a significant long-run relationship between economic growth and bank credit extension. The Granger causality test provides evidence of unidirectional causal relationship with direction from economic growth to credit extension for South Africa. The study results indicate that the case for demand-following hypothesis is stronger than supply-leading hypothesis in South Africa. Economic growth spurs credit market development in South Africa. Overall, the results show that there is a stable long-run relationship between macroeconomic business cycles and real credit growth in South Africa. The results show that economic growth significantly causes and stimulates bank credit. The study, therefore, recommends that South Africa needs to give policy priority to promotion and development of the real sector of the economy to propel and accelerate credit extension. Economic growth is considered as the significant policy variable to stimulate credit extension. The findings therefore hold important implications for both theory and policy. / Business Management / D.B.L.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / One of the main causes of control loop performance degradation are the oscillations, which have a negative effect on the performance of these loops and may force the plant to operate at less than optimal conditions. One of the fundamental steps for the evaluation of industrial control loop performance is the detection and diagnosis of these oscillations, also motivated by the growing emphasis on security and earnings capacity of the installations. This paper uses wavelet analysis combined with other signal analysis techniques such as the autocorrelation function and the Granger Causality, to make the complete diagnosis of oscillations in control loops processes. Numerical test simulations are presented to demonstrate the effectiveness of the proposed method. First, the techniques are used for the diagnosis of a simple control loop in the format of internal model control. After, the methods are applied in a catalytic cracking unit operating under model predictive control (MPC). The results show the potentiality of the proposed methodology to real applications. / Uma das principais causas da degradação do desempenho em malhas de controle são as oscilações, as quais têm um efeito negativo sobre o desempenho dessas malhas e pode forçar a planta a operar em condições abaixo do ideal. Um dos passos fundamentais para a avaliação do desempenho de malhas de controle industriais são a detecção e diagnóstico dessas oscilações, motivados também pela crescente ênfase na segurança e capacidade de lucro das instalações. O presente trabalho usa a análise de Wavelet combinada com outras técnicas de análise de sinais, tais como a Função de Autocorrelação e a Causalidade de Granger, para fazer o diagnóstico completo de oscilações em malhas de controle de processos. Testes de simulações numéricas são apresentados para demonstrar a eficácia da metodologia proposta. Primeiramente, as técnicas são utilizadas para o diagnóstico de uma malha de controle simples no formato de controle por modelo interno. Posteriormente, os métodos são aplicados numa unidade de craqueamento catalítico operando sob controle preditivo (MPC). Os resultados obtidos mostram a potencialidade da metodologia proposta para aplicações reais.

Submitted by Karla Malafaia (karlamalafaia@gmail.com) on 2013-02-26T23:31:57Z No. of bitstreams: 1 Tese_Karla_Malafaia_VF_posbanca.pdf: 730119 bytes, checksum: 82ceecb815ca22f5f1e5fee680caf839 (MD5) / Approved for entry into archive by Vera Lúcia Mourão (vera.mourao@fgv.br) on 2013-02-27T13:25:04Z (GMT) No. of bitstreams: 1 Tese_Karla_Malafaia_VF_posbanca.pdf: 730119 bytes, checksum: 82ceecb815ca22f5f1e5fee680caf839 (MD5) / Made available in DSpace on 2013-02-27T13:29:38Z (GMT). No. of bitstreams: 1 Tese_Karla_Malafaia_VF_posbanca.pdf: 730119 bytes, checksum: 82ceecb815ca22f5f1e5fee680caf839 (MD5) Previous issue date: 2013-01-29 / Este trabalho se propõe a testar e quantificar a importância do investimento de longo prazo, captado pela série de desembolsos da linha BNDES Finem, na produção industrial brasileira. Através dos modelos de causalidade de Granger e Função resposta ao impulso, podemos verificar as respostas acumuladas ao longo de três anos da linha Finem a choques positivos de um desvio padrão nas variáveis inflação, produção industrial, spread, e, da mesma forma um choque na variável Finem com resposta nas variáveis acima descritas. Além disso, é possível identificar a importância do BNDES como um ator anticíclico em períodos de crise como na economia brasileira. Como resultado, encontramos que apesar dos desembolsos Finem não Granger causarem a produção industrial brasileira, se testadas em conjunto com dados de inflação e a diferença entre a Selic e a TJLP rejeita-se a hipótese nula de não causalidade a 1% de significância. Já os testes de funções de resposta ao impulso indicam que a taxa de crescimento da produção industrial tem resposta positiva a um choque de desvio padrão nos desembolsos de Finem. Contudo, se testada em conjunto um choque no Finem apesar de impactar positivamente a produção industrial acaba pressionando a inflação. / This work is to test and quantify the importance of a long-term investment captured by the series of disbursements of BNDES Finem line in brazilian industrial production. Through Granger causality and impulse-response function, it was possible to check the Finem line accumulated answers along three years to positive shocks of a standard deviation on the variables inflation, industrial production, spread, and a shock on Finem variable with answer on the previous described variables. Furthermore, it's possible to identify the BNDES's importance as a countercyclical tool in crisis period as in brazilian economy. As a result, we found that despite causing the brazilian industrial production, if the no Granger Finem's disbursements are tested with inflation data and the difference between Selic and TJLP, the null hypothesis of no causality at 1% of significance is rejected. Yet, the tests of impulse-response function indicate that the industrial production growth rate has positive answer to a shock of standard deviation on Finem's disbursements. However, despite impacting the industrial production positevely, it pressures the inflation if it's tested with a shock on Finem.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Globalization provoked in financial markets by means stock exchanges an interchange among the markets over the world. The aim of this study was to examine the relationship of the ten major main economic index of the world represented in New York (DJIA, S&P500 e Nasdaq), Tokyo (NIKKEI 225), London (FSTE 100), São Paulo (IBOV), Shanghai (SSE180), Paris (CAC-40), Frankfurt (DAX-30) and Buenos Aires (Merval) and looking for its co-integration, to demonstrate the behavior of these indexes and the long run equilibrium, from January of 2010 to March of 2011. To investigate the equilibrium and the long rum behavior the error correction model was used jointly with co-integration test and impulse response based on Cholesky decomposition. The results of this study show that the index of stock markets has long term equilibrium, and American markets, Argentina and English showed a strong influence over other markets. With this research we can infer that a relationship exists between the stock markets under study, confirming that the economy in a country can influence the others. In this sense, the contribution of this study, given this range of discussions involving the interconnection of economies with respect to trades made on the stock exchanges, was to show the relationships and influences in the world. / A internacionalização somada à abertura dos mercados financeiros transformou as economias antes fechadas em economias abertas, provocou um intercâmbio entre as economias mundiais por meio das bolsas de valores. O objetivo deste estudo é examinar a relação entre os dez principais índices econômicos do mundo, sendo eles: Nova York (DJIA, S&P500 e Nasdaq), Tóquio (Nikkei 225), Londres (FSTE 100), São Paulo (IBOV), Shangai (SSE180), Paris (CAC), Frankfurt (DAX-30) e Bueno Aires (Merval), por meio da análise de co-integrações para demonstrar o comportamento desses índices e seus equilíbrios no período de janeiro de 2010 a março de 2011. Para investigar e verificar o comportamento em longo prazo, foi utilizado o modelo de correção de erros e teste de impulso-resposta baseado na decomposição de Cholesky. Os resultados deste estudo mostram que existe equilíbrio em longo prazo entre os índices do mercado de ações. Os mercados americano, argentino e inglês mostraram forte influência sobre os demais mercados. Com esta pesquisa, verifica-se que existe uma relação entre os mercados de ações estudados, confirmando que a economia de um país influencia as demais. A contribuição deste estudo é verificar a assertiva das discussões atuais sobre a dependência das economias mundiais com as negociações por meio da bolsa de valores.

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.

This essay examines the relationship between exchange rate volatility, estimated using a GARCH model, and level of trade for Sweden and Finland. The data used was collected from Refinitive Eikon Datastream with monthly observations for the time period January 2005 - December 2022. The obtained results indicate that the volatility of the Swedish Krona and Euro positively increases the level of trade for Sweden respectively Finland according to the ARDL model. However, while examining different time perspectives the conclusions resulted in inconclusiveness for the countries and perspectives. The ARDL bounds test for Sweden corresponded with inconclusive results regarding a possible positive long term relationship between SEKs exchange rate volatility and level of trade. Furthermore, the Granger causality test did not state a short term relationship between the two variables for Sweden nor did it state a reversed relationship. On the other hand, for Finland, the ARDL bounds test and Granger causality test denied both a long term and short term positive relationship between the EURs exchange rate volatility and level of trade for Finland. However, for Finland a reversed Granger causality test was shown indicating that the level of trade has an impact on the volatility of the EURs exchange rate.

Der technologische Fortschritt hat in jüngster Zeit zu einer großen Zahl von Zeitreihenmessdaten über komplexe dynamische Systeme wie das Klimasystem, das Gehirn oder das globale ökonomische System geführt. Beispielsweise treten im Klimasystem Prozesse wie El Nino-Southern Oscillation (ENSO) mit dem indischen Monsun auf komplexe Art und Weise durch Telekonnektionen und Rückkopplungen in Wechselwirkung miteinander. Die Analyse der Messdaten zur Rekonstruktion der diesen Wechselwirkungen zugrunde liegenden kausalen Mechanismen ist eine Möglichkeit komplexe Systeme zu verstehen, insbesondere angesichts der unendlich-dimensionalen Komplexität der physikalischen Prozesse. Diese Dissertation verfolgt zwei Hauptfragen: (i) Wie können, ausgehend von multivariaten Zeitreihen, kausale Wechselwirkungen praktisch detektiert werden? (ii) Wie kann die Stärke kausaler Wechselwirkungen zwischen mehreren Prozessen in klar interpretierbarer Weise quantifiziert werden? Im ersten Teil der Arbeit werden die Theorie zur Detektion und Quantifikation nichtlinearer kausaler Wechselwirkungen (weiter-)entwickelt und wichtige Aspekte der Schätztheorie untersucht. Zur Quantifikation kausaler Wechselwirkungen wird ein physikalisch motivierter, informationstheoretischer Ansatz vorgeschlagen, umfangreich numerisch untersucht und durch analytische Resultate untermauert. Im zweiten Teil der Arbeit werden die entwickelten Methoden angewandt, um Hypothesen über kausale Wechselwirkungen in Klimadaten der vergangenen hundert Jahre zu testen und zu generieren. In einem zweiten, eher explorativen Schritt wird ein globaler Luftdruck-Datensatz analysiert, um wichtige treibende Prozesse in der Atmosphäre zu identifizieren. Abschließend wird aufgezeigt, wie die Quantifizierung von Wechselwirkungen Aufschluss über mögliche qualitative Veränderungen in der Klimadynamik (Kipppunkte) geben kann und wie kausal treibende Prozesse zur optimalen Vorhersage von Zeitreihen genutzt werden können. / Today''s scientific world produces a vastly growing and technology-driven abundance of time series data of such complex dynamical systems as the Earth''s climate, the brain, or the global economy. In the climate system multiple processes (e.g., El Nino-Southern Oscillation (ENSO) or the Indian Monsoon) interact in a complex, intertwined way involving teleconnections and feedback loops. Using the data to reconstruct the causal mechanisms underlying these interactions is one way to better understand such complex systems, especially given the infinite-dimensional complexity of the underlying physical equations. In this thesis, two main research questions are addressed: (i) How can general causal interactions be practically detected from multivariate time series? (ii) How can the strength of causal interactions between multiple processes be quantified in a well-interpretable way? In the first part of this thesis, the theory of detecting and quantifying general (linear and nonlinear) causal interactions is developed alongside with the important practical issues of estimation. To quantify causal interactions, a physically motivated, information-theoretic formalism is introduced. The formalism is extensively tested numerically and substantiated by rigorous mathematical results. In the second part of this thesis, the novel methods are applied to test and generate hypotheses on causal interactions in climate time series covering the 20th century up to the present. The results yield insights on an understanding of the Walker circulation and teleconnections of the ENSO system, for example with the Indian Monsoon. Further, in an exploratory way, a global surface pressure dataset is analyzed to identify key processes that drive and govern interactions in the global atmosphere. Finally, it is shown how quantifying interactions can be used to determine possible structural changes, termed tipping points, and as optimal predictors, here applied to the prediction of ENSO.

Das Kausalitaetskonzept von Granger und die Impuls-Antwort-Analyse sind zwei Konzepte, die haeufig verwendet werden, um kausale Beziehungen zwischen zwei Variablen in vektorautoregressiven (VAR) Modellen zu untersuchen. Wenn das VAR Modell mehr als zwei Variablen umfasst, besteht eine Erweiterung des Standard Granger Kausalitaetskonzepts darin, Kausalitaet an hoeheren Prognosehorizonten zu messen. Die Kausalitaetsbeziehungen unter diesem erweiterten Granger Kausalitaetskonzept werden mit denen bei Standard Granger Kausalitaet (Ein-Schritt-Prognose) und mit Kausalitaet im Sinne der Impuls-Antwort-Analyse verglichen. Es wird insbesondere dargestellt, inwiefern das erweiterte Granger Kausalitaetskonzept als Verallgemeinerung der letztgenannten Konzepte aufgefasst werden kann. Wenn Kausalitaet an Prognosehorizonten groesser als eins gemessen wird und das VAR Modell mehr als zwei Variablen umfasst, impliziert die Nullhypothese, dass eine Variable nicht kausal fuer eine andere Variable sei, nichtlineare Restriktionen auf die VAR Koeffizienten. (In nichtstationaeren VAR Modellen treten nichtlineare Restriktionen sogar schon unter dem Standard Granger Kausalitaetskonzept auf.) Aufgrund der speziellen Form der Restriktionen kann es vorkommen, dass die Standard Wald Statistik nicht mehr die uebliche, asymptotische Chiquadrat-Verteilung hat. Dieses Problem wird im allgemeinen in der Praxis ignoriert. Beispiel 4.1, Proposition 4.1 und Korollar 4.1 zeigen jedoch, dass dieses Problem nicht irrelevant ist. Zwei Loesungen werden in Proposition 5.1 und Proposition 5.2 in Form eines randomisierten Wald Tests sowie eines Wald Tests mit verallgemeinerter Inverse angeboten. In einer anschliessenden kleinen Simulationsstudie werden Groesse und Macht dieser modifizierten Wald Tests relativ zu der des Standard Wald Tests untersucht fuer verschiedene stationaere trivariate VAR(1)-Modelle. In einem kurzen Ueberblick werden zudem Vor- und Nachteile alternativer Testverfahren (Bootstrap, sequentielle Tests) zusammengefasst. / The concepts of standard Granger causality and impulse response analysis are often used to investigate causal relationships between variables in vector autoregressive (VAR) models. In VAR models with more than two variables, the concept of standard Granger causality can be extended by studying prediction improvement at forecast horizons greater than one. The causal relationships which arise under this extended Granger causality concept are compared to those arising under the standard Granger causality concept (one-step forecasts) and those arising with impulse-response-analysis. In particular, it is illustrated inhowfar the extended Granger causality concept can be understood as a generalization of the standard Granger causality concept and even of impulse-response-analysis. If causality is measured at forecast horizons greater than one, and if there are more than two variables in the VAR system, the null hypothesis that one variable is not causal for another variable implies restrictions which are a nonlinear function of the VAR coefficients. (In nonstationary VAR models, nonlinear restrictions already arise under the standard Granger causality concept.) Due to the special form of the restrictions, the standard Wald test may no longer have the usual asymptotic chisquare-distribution under the null hypothesis. This problem is commonly neglected in practice. However, Example 4.1, Corollary 4.1 and Proposition 4.1 of this thesis illustrate that this problem is not irrelevant. Furthermore, Propositions 5.1 and 5.2 show that this problem may be overcome, at least in stationary VAR models, by using either a randomized Wald test or a Wald test with generalized inverse. Size and Power of these modified Wald tests relative to the standard Wald test are investigated in a small simulation study for different stationary, trivariate VAR(1) models. Moreover, the pros and cons of alternative testing strategies (bootstrap, sequential tests) are summarized in a brief overview.

Financial liberalisation, through increasing investment as well as the average productivity of capital, should stimulate economic growth, or so the theory goes. Bank lending unfortunately suffers adverse selection and moral hazard effects, to which the establishment and expansion of stock markets has been offered as a remedy. However, research from developing country stock markets have shown that in many cases these markets did not complement the effects of credit market liberalisation but in rather important aspects subverted them. Countries that implemented credit market liberalisation and raised real interest rates only increased the price of debt capital rather than all capital. This caused a share price boom in many of them. When the price of equity capital fell it seriously undermined and indeed allowed large private corporations to skip altogether the main channel of high interest rates through which the theoretical McKinnon-Shaw effects were to operate. This study asks the research question of what effect the expansion of the South African stock exchange has had for its economic development. It makes use of a general empirical model to explain the relationship between financial development and real output. The model comprises indicators for growth, banking system development, stock market volatility; and, stock market development through a conglomerate index that accounts for market size, liquidity and integration with world capital markets. Quarterly data from 1989 to 2001 is analysed based on the null hypothesis that, as far as financial architecture is concerned, the development of the JSE Securities Exchange has stimulated the country's economic growth. This study found a negative and statistically significant relation between stock market development and economic growth. It suggests that while the JSE Securities Exchange is a relatively large stock market it is the presence of thin trading that prevents the proposed benefits of market development from accruing to the economy. Thus the hypothesis is rejected. However, since the only stable cointegrating vector is between growth and banking sector development, it recommends that by expanding their universal banking functions, the present banking structure, though oligopolistic, may be better suited to act as a catalyst for growth. / Business Management / D. Comm.