1 Abstract In this thesis, we present an empirical analysis of integration between the Baltic and global stock markets during the period between 2000 and 2018. This research is spurred by the fact that all three Baltic countries displaying similar positive economic developments over the studied horizon. Using the theoretical and empirical findings from similar research papers, we ground our work for the analysis. Our methodology is based on three different models: DCC-GARCH, total and frequency connectedness, and the Engle-Granger cointegration test. Using these methods, we are able to determine both short- or long-term relationship dynamics. Based on the results from our empirical analysis we were not able to reject the null hypotheses, that the Baltic states have become more integrated between themselves and the global market. At best, our results would suggest a weak form of integration given that there were indeed some notable dynamic changes. Following these results, we provide insight on interdependencies between the Baltic states and their relationships with the global stock markets. Most notable dynamics are captured by the total connectedness measure, which indicates that the Baltic stock markets show a significantly increased connectedness with the global indices, during turbulent times in the...

A pesquisa apresenta um estudo sobre a superioridade dos analistas de mercado com relação aos modelos random walk na previsão de resultados futuros das empresas brasileiras de capital aberto a curto e longo prazo. A literatura tradicional indica superioridade irrestrita dos analistas de mercado sobre os modelos de séries temporais por conta das vantagens de tempo e informação desses agentes. No entanto, estudos recentes da literatura internacional apontam para a necessidade de reavaliação dessa superioridade indicando que, para determinadas características da empresa e principalmente para estimativas de longo prazo, não se verifica superioridade dos analistas com relação aos modelos de séries temporais. Partindo desses achados, essa pesquisa defende a TESE de que para o caso brasileiro a superioridade dos analistas não é irrestrita. Este trabalho avalia as previsões de lucro dos analistas e dos modelos random walk, simples e com crescimento, a curto e longo prazo, para as empresas brasileiras de capital aberto no período de 2010 a 2015. Os dados foram obtidos via plataforma da Thomson Reuters®, nas bases de dados do I/B/E/S® e Thomson Financial. Seguindo a literatura, foram utilizados testes de diferença de média. Como diferencial da pesquisa, foi realizada uma análise de dados em painel no sentido de permitir uma avaliação mais precisa sobre os determinantes da superioridade dos analistas para o caso brasileiro. Ainda, foi proposto um modelo de regressão linear simples para avaliar o conteúdo informacional das previsões dos analistas de mercado e dos modelos random walk. Os resultados indicam: i) maior acurácia de previsão paras os modelos random walk simples quando comparados com os modelos de random walk com crescimento; ii) para a amostra total, nota-se maior acurácia da previsão dos modelos random walk a curto e longo prazo, com superioridade dos analistas apenas para previsões com três meses de defasagem; iii) além da defasagem de previsão, a variabilidade dos lucros, a quantidade de analistas, a dispersão das estimativas dos analistas, o tamanho da empresa, o resultado positivo ou negativo, a listagem em índice de mercado e a idade da empresa no mercado de capitais são fatores que alteram a superioridade dos analistas para o caso brasileiro; iv) maior conteúdo informacional das previsões random walk para previsão de lucros futuros das empresas. Esses resultados são importantes nas decisões de investimento. Ainda, os achados são relevantes para pesquisas da área de finanças e contabilidade que utilizam essa variável para responder a diferentes questões de pesquisa, uma vez que, ao contrário do apontado pela literatura internacional, as evidências sugerem superioridade de previsão dos modelos random walk quando comparados às previsões dos analistas de mercado / The research presents a study regarding the superiority of market analysts in relation to the random walk models in the forecast of future results of Brazilian companies in the short and long term. The traditional literature indicates unrestricted superiority of market analysts on time series models because of the time and information advantages of these agents. However, recent studies in the international literature point to the need for a reassessment of this superiority, indicating that, for certain company characteristics and especially for long-term estimates, there is no superiority of analysts with respect to time series models. Based on these findings, this research advocates that in the case of Brazil, the superiority of analysts is not unrestricted. This paper evaluates the analysts\' forecasts and the random walk models, both simple and with growth, in the short and long term, for Brazilian publicly traded companies during the period from 2010 to 2015. Data was obtained via the Thomson Reuters® platform, in the I/B/E/S® and Thomson Financial®databases. Following the literature, mean-comparison tests (t-test) were used. As a research differential, a panel data analysis was carried out in order to allow a more precise evaluation of the determinants of analysts\' superiority for the case of Brazil. Furthermore, a simple linear regression model was proposed to evaluate the informational content of market analysts\' forecasts and random walk models. The results indicate: i) greater accuracy of prediction for the simple random walk models, when compared to the random walk models with growth ii) that for the total sample, we can see a greater accuracy of the forecast of random walk models in the short and long term, with analyst superiority only for forecasts with a 3-month lag; (iii) in addition to forecast lag, profit variability, analyst size, dispersion of analysts\' estimates, company size, positive or negative result, market index listing and age of the company in the capital market are factors that alter the superiority of the analysts in the case of Brazil; iv) greater informational content of the random walk forecasts for the prediction of future companies\' profits. These results are important for investment decisions. Moreover, the findings are relevant for research in the field of finance and accounting that use this variable to answer different research questions, since, contrary to the international literature, the evidence suggests forecasting superiority of the random walk models when compared to the market analysts\' forecasts.

A pesquisa apresenta um estudo sobre a superioridade dos analistas de mercado com relação aos modelos random walk na previsão de resultados futuros das empresas brasileiras de capital aberto a curto e longo prazo. A literatura tradicional indica superioridade irrestrita dos analistas de mercado sobre os modelos de séries temporais por conta das vantagens de tempo e informação desses agentes. No entanto, estudos recentes da literatura internacional apontam para a necessidade de reavaliação dessa superioridade indicando que, para determinadas características da empresa e principalmente para estimativas de longo prazo, não se verifica superioridade dos analistas com relação aos modelos de séries temporais. Partindo desses achados, essa pesquisa defende a TESE de que para o caso brasileiro a superioridade dos analistas não é irrestrita. Este trabalho avalia as previsões de lucro dos analistas e dos modelos random walk, simples e com crescimento, a curto e longo prazo, para as empresas brasileiras de capital aberto no período de 2010 a 2015. Os dados foram obtidos via plataforma da Thomson Reuters®, nas bases de dados do I/B/E/S® e Thomson Financial. Seguindo a literatura, foram utilizados testes de diferença de média. Como diferencial da pesquisa, foi realizada uma análise de dados em painel no sentido de permitir uma avaliação mais precisa sobre os determinantes da superioridade dos analistas para o caso brasileiro. Ainda, foi proposto um modelo de regressão linear simples para avaliar o conteúdo informacional das previsões dos analistas de mercado e dos modelos random walk. Os resultados indicam: i) maior acurácia de previsão paras os modelos random walk simples quando comparados com os modelos de random walk com crescimento; ii) para a amostra total, nota-se maior acurácia da previsão dos modelos random walk a curto e longo prazo, com superioridade dos analistas apenas para previsões com três meses de defasagem; iii) além da defasagem de previsão, a variabilidade dos lucros, a quantidade de analistas, a dispersão das estimativas dos analistas, o tamanho da empresa, o resultado positivo ou negativo, a listagem em índice de mercado e a idade da empresa no mercado de capitais são fatores que alteram a superioridade dos analistas para o caso brasileiro; iv) maior conteúdo informacional das previsões random walk para previsão de lucros futuros das empresas. Esses resultados são importantes nas decisões de investimento. Ainda, os achados são relevantes para pesquisas da área de finanças e contabilidade que utilizam essa variável para responder a diferentes questões de pesquisa, uma vez que, ao contrário do apontado pela literatura internacional, as evidências sugerem superioridade de previsão dos modelos random walk quando comparados às previsões dos analistas de mercado / The research presents a study regarding the superiority of market analysts in relation to the random walk models in the forecast of future results of Brazilian companies in the short and long term. The traditional literature indicates unrestricted superiority of market analysts on time series models because of the time and information advantages of these agents. However, recent studies in the international literature point to the need for a reassessment of this superiority, indicating that, for certain company characteristics and especially for long-term estimates, there is no superiority of analysts with respect to time series models. Based on these findings, this research advocates that in the case of Brazil, the superiority of analysts is not unrestricted. This paper evaluates the analysts\' forecasts and the random walk models, both simple and with growth, in the short and long term, for Brazilian publicly traded companies during the period from 2010 to 2015. Data was obtained via the Thomson Reuters® platform, in the I/B/E/S® and Thomson Financial®databases. Following the literature, mean-comparison tests (t-test) were used. As a research differential, a panel data analysis was carried out in order to allow a more precise evaluation of the determinants of analysts\' superiority for the case of Brazil. Furthermore, a simple linear regression model was proposed to evaluate the informational content of market analysts\' forecasts and random walk models. The results indicate: i) greater accuracy of prediction for the simple random walk models, when compared to the random walk models with growth ii) that for the total sample, we can see a greater accuracy of the forecast of random walk models in the short and long term, with analyst superiority only for forecasts with a 3-month lag; (iii) in addition to forecast lag, profit variability, analyst size, dispersion of analysts\' estimates, company size, positive or negative result, market index listing and age of the company in the capital market are factors that alter the superiority of the analysts in the case of Brazil; iv) greater informational content of the random walk forecasts for the prediction of future companies\' profits. These results are important for investment decisions. Moreover, the findings are relevant for research in the field of finance and accounting that use this variable to answer different research questions, since, contrary to the international literature, the evidence suggests forecasting superiority of the random walk models when compared to the market analysts\' forecasts.

[pt] Na presente dissertação, além de se expor a fundamentação teórica das Metodologias Estruturais clássica e bayesiana para previsão de séries temporais, analisou-se o comportamento de séries temporais, analizou-se o comportamento da série produção de sacos de polipropileno produzidos pela Indústria Têxtil Oeste Ltda. com observações cobrindo o período de janeiro de 1987 a junho de 1992. Na análise, através dos pacotes computacionais correspondentes: STAMP (clássico) e BATS (bayesiano), utilizou-se variáveis de intervenção e a variável exógena correspondente à produção de metros quadrados de polipropileno, cobrindo período idêntico, ou seja janeiro de 1987 a junho de 1992. Adotando como critério de decisão o erro médio quadráticas previsões no período de ajuste e da análise ex-ante feita com as seis últimas observações (janeiro a junho de 1992), para testar a capacidade extrapolativa dos modelos, escolheu-se um modelo representativo dentro de cada abordagem e em seguida foi feito um estudo comparativo de ambas. / [en] In the present dissertation, besides exposing the theoretical foundations of Structural Models (Classic and Bayesian approaches); we also analysed the series of production of propileno´s bag produced by Indústria Têxtil Oeste Ltda. with observation covering the period from January 1987 to June 1992. We used in the analysis the packages: STAMP (classical) and BATS (Bayesian), with intervention variables and the series of production of square meters of propileno as explanatory variable. As decision criterion we used the mean square error during the period of adjustment and the ex-ante analysis with the last six observation (January up to June of 1992), to test the predictive ability of the models.

[pt] O Modelo Estrutural, recentemente desenvolvido por Harvey, considera a tradicional idéia de modelar uma série a partir de suas componentes básicas não observadas. Em particular, a componente cíclica, que descreve um movimento senoidal amortecido, pode ser utilizada para explicar um comportamento repetitivo ao longo da série. O uso desta componente é motivado pelo fato de que o seu espectro teórico apresenta um pico de valor finito. O modelo original de Harvey define o ciclo da série a partir de uma única senóide amortecida. Porém, a estimação do espectro de algumas séries reais revelou ser razoável supor que a componente cíclica de tais séries representa uma soma de várias senóides amortecidas em diferentes seqüências. Neste trabalho é proposta uma extensão da componente cíclica para o modelo de Harvey e discute-se, para o modelo estendido, a estrutura ARIMA equivalente. Constrói-se um teste de multiplicadores de Lagrange no domínio da freqüência, com o objetivo de verificar a existência de uma freqüência adicional na estrutura do ciclo. Finalmente, a teoria apresentada na dissertação é aplicada de forma a testar a presença de uma segunda freqüência no ciclo da série de índices pluviométricos de Fortaleza. / [en] The Structural Models, recently suggested by Harvey, uses the classic idea of modelling a time series y its non observed components. The cyclical component of the series, which is defined by a smoothed sine, is a special one that may be used for explaining a repetitive behaviour along the series. The motivation for using this component lies in the finite valued peak presnted by its theoretic spectrum. Harvey´s model stays that the cycle of the series is defined by a single smoothed sine. However, the estimated spectrum of certain series showed that it is reasonable to suppose the cyclical component of those series as being a sum of distinct smoothed sines of different frequencies. This thesis proposses an extension of the cyclical component in Harvey´s model and discusses the equivalent ARIMA structure for this extended component. We develop a Lagrange Multipliers test in the frequence domain for verifying the existence of an extra frequence in the cyclical component. The theory presented in the dissertation is applied with the purpose of testing the presence of a second frequence in the cycle of the series of sunspot numbers and in the series of rainfall in Fotaleza.

One fundamental point of departure for this thesis is the importance of addressing all three basic economic research questions: what is produced, with what and for whom and including them in the discussion regarding long-term macroeconomic performance. This could also be stated as that a consistent historical national accounts approach where both aspects of production and distribution are included can significantly enhance the research on macroeconomic historical issues. Built upon this foundation, the objective of this thesis is twofold. To begin with, the objective includes the broadening of the empirical database of the Swedish historical national accounts (SHNA) with accounts for the process involving the horizontal distribution of income. The second objective of this thesis consists of conducting analyses of the Swedish macroeconomic devel­opment using the extended database of the SHNA. An important aspect of the analytical objective involves the exploration of methods that had not widely been applied in Swedish economic historical research. Thus, great emphasis is placed on the methodology used in the analyses of macroeconomic development. These two main objectives forni the disposition of the thesis. The first empirical part consists of work with income accounts in the SHNA. This work has resulted in the establishment of a set of income accounts concur­ring with the procedure recommended in the contemporary national accounting system. In the second part of the thesis, selected macroeconomic issues are examined using the extended SHNA database. The first analysis consists of a closer examination of the presence of periodization patterns in Swedish growth and structural change. In this chapter an analysis based on structural time series models is applied to the SHNA series. The main results of this chapter is that the time series on growth and structural change reveal a pattern that not unconditionally is consistent with the prevailing periodisation pattern recognised in Swedish economic-historical research. Instead, the development pattern reveals features found in international research. The next analysis is concerned with the role of specific institutions for contributing to the slow-down in growth that occurred from the late 1960s and throughout the 1970s and 1980s. In this chapter the importance of the corporate tax system, investment funds and the public pension funds for the efficiency of the resource alloca­tion process is examined. The hypothesis that is examined is that these institutional arrangements altered the distribution of income in such a way that the investment allocation was disturbed and thereby leading to ineffi­ciencies that affected long-term growth negatively. This hypothesis is supported by empirical evidence on changes in the income distribution and changes in long-term rates of growth and structural change. Thus, the investigated institutional arrangements to a certain extent had a negative effect on the Swedish economic per­formance during the 1960s to the 1980s. In the final analytical chapter, the objective is mainly methodological. Here, the focus is on the potential application of CGE-models as a tool for examining Swedish macroeconomic history. A fairly straightforward CGE-model is formulated for the period 1910 to 1930 and estimated using the broadened SHNA. The predic­tions of the model are evaluated against the actual historical development in order to assess the performance of the model. As the model formulated in this chapter generates accurate prediction of the main macroeconomic indicators, it is subsequently used in a counterfactual analysis of the impact of total factor productivity growth on the overall growth performance. In summary, the thesis demonstrates that much can be achieved in the research on the Swedish macroeco­nomic development by utilizing new theoretical approaches and applying state of the art analysis methods as a complement to the structural analytical research that has been conducted previously. However, much research is still required, especially on the improvement of the macroeconomic database where one priority is to create detailed and consistent input-output tables and social accounting matrices. / digitalisering@umu

<p>This study investigates cattle futures response to the equities crash in March of 2020 and the subsequent COVID-19 linked production delays at beef packing plants. I observe that the initial declines in cattle futures began prior to the onset of beef packing plant shutdowns. Fitting a Vector Error Correction Model on live cattle futures, feeder cattle futures, and corn futures to the E-Mini S&P 500 futures contract finds evidencethat the S&P 500 had a significant impact on cattle prices during  March  of  2020.  These  results  are  an  example  of  increased  cross-asset  correlation  during periods of financial distress.</p>

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參考Fang 2003年研究方法架構，我們檢驗了結合策略(結合技術分析法則和時間序列模型)應用在六個亞洲股票市場。由於技術分析法則和時間序列模型皆可利用過去歷史資訊來預測報酬，所以結合策略的實證結果優於技術分析法則和時間序列模型。此篇中超額報酬的計算是與買進持有相比較下未考慮交易成本的超額報酬。實證結果顯示，結合策略在完整樣本中可以成功的預測資產報酬，在六個國家的平均上，結合策略的超額報酬為0.19%優於技術交易法則下的0.13%和時間序列模型下的0.17%。並且，發現在新興國家如台灣、泰國、馬來西亞和南韓的預測能力比在已開發國家市場如香港和日本還要來的好。預測能力可被低階的自我相關係數解釋。除此之外，發現我們的預測能力受到非同步交易的影響。非同步交易所造成的衡量誤差使得超額報酬下降，但是我們的預測能力還是存在的。 / Following Fang and Xu (2003), we examine trading strategies combining technical trading rules and times series forecasts on six Asian stock markets. Since both technical trading rules and time series models can exploit predictable components as function of past prices or returns, the combined strategies outperform both technical trading rules and time series forecasts. The excess returns before transaction costs for each rule and country are compared to a passive buy-and-hold strategy. The combined strategies are quite successful in predicting asset returns in full samples. On average the buy-sell returns for combined strategies are 0.19% much higher than 0.13% for technical trading rules and 0.17% for time series models. Besides, we also find that all three rules have more explanatory power in emerging markets such as Taiwan, Thailand, Malaysia and Korea than more developed markets such as Japan and Hong Kong. The predictability can be explained by significant low-order autocorrelations in returns. Moreover, excess returns (pre-trading costs) for both time series models and combined strategies can be partially attributed to the measurement errors arising from non-synchronous trading. The non-synchronous trading bias reduces but does not eliminate the predictive power of combined strategies.

This thesis, “Empirical Asset Pricing and Investment Strategies”, examines a number of topics related to portfolio choice, asset pricing, and strategic and tactical asset allocation. The first two papers treat the predictability of asset returns. Since at least the mid-1980s until quite recently, the conventional wisdom has been that it is possible to predict the return on, for example, an index of stocks. However, a series of recent papers have challenged this conventional wisdom. I answer this challenge and show that it is possible to predict returns if structural changes in the underlying economy are taken into account. The third paper examines the comovement between stocks and bonds. I show how it is possible to improve the composition of a portfolio consisting of these two asset classes by taking into account how the comovement changes over time. All three papers are self-contained and can therefore be read in any order. The first paper is entitled “Structural Breaks in Asset Return Predictability: Can They Be Explained?” Here I investigate whether predictability has changed over time and, if so, whether it is possible to tie the change to any underlying economic variables. Dividend yield and the short interest rate are often used jointly as instruments to predict the return on stocks, but several researchers present evidence that the relation has undergone a structural break. I use a model that extends the conventional structural breaks models to allow both for smooth transitions from one state to another (with a break as a special case), and for transitions that depend on a state variable other than time. The latter allows me to directly test whether, for example, the business cycle influences how the instruments predict returns. The results suggest that this is not the case. However, I do find evidence of a structural change primarily in how the instruments predict returns for large firms. The change differs from a break in that it appears to be an extended non-linear transition during the period 1993—1997. After the change, the short rate does not predict returns at all. Dividend yield, on the other hand, is strongly significant, and the return has become more sensitive to it. In the second paper, “Restoring the Predictability of Equity Returns,” I take another perspective on predictability and structural shifts. Several recent papers have questioned the predictability of equity returns, potentially implying serious negative consequences for investment decision-making. With return data including the 1990s, variables that previously predicted returns, such as the dividend yield, are no longer significant and results of out-of-sample tests are often weak. A possible reason is that the underlying structure of the economy has changed. I use an econometric model that allows for regime shifts over time as well as due to changes in a state variable, in this case the price-earnings ratio. This makes it possible to separate influences from these two sources and to determine whether one or both sources have affected return predictability. The results indicate that, first, a structural change occurred during the 1990s, and, second, that the unusually high level of price earnings in the late 1990s and early 2000s temporarily affected predictability at the 12-month horizon. In the third paper, “Coupling and Decoupling: Changing Relations between Stock and Bond Market Returns,” I investigate stock-bond comovement. The correlation between stocks and bonds has changed dramatically over the last ten years, introducing a new type of risk for portfolio managers, namely, correlation risk. I use GARCH estimates of stock volatility, simple regressions, and regime-switching econometric models to assess whether level of volatility, or changes in volatility, can be used to explain some of the changes in comovement in seven different countries. As regards volatility level, strong support is found in almost all countries to suggest that high volatility predicts lower, or negative, comovement. I argue that this can be evidence of a market-timing type of behavior. As for changes in volatility, the results are more mixed. Only for the U.S. market do I find strong support to conclude that large changes tend to coincide with lower, or negative, comovement. This could be evidence of a flight-to-quality (or cross-market hedging) type of behavior. / <p>Diss. Stockholm : Handelshögskolan, 2007</p>