This thesis applies entropy as a model independent measure to address research questions concerning the dynamics of various financial time series. The thesis consists of three main studies as presented in chapters 3, 4 and 5. Chapters 3 and 4 apply an entropy measure to conduct a bivariate analysis of drawdowns and drawups in foreign exchange rates. Chapter 5 investigates the dynamics of investment strategies of hedge funds using entropy of realised volatility in a conditioning model. In all three studies, methods from information theory are applied in novel ways to financial time series. As Information Theory and its central concept of entropy are not widely used in the economic sciences, a methodology chapter was therefore included in chapter 2 that gives an overview on the theoretical background and statistical features of the entropy measures used in the three main studies. In the first two studies the focus is on mutual information and transfer entropy. Both measures are used to identify dependencies between two exchange rates. The chosen measures generalise, in a well defined manner, correlation and Granger causality. A different entropy measure, the approximate entropy, is used in the third study to analyse the serial structure of S&P realised volatility. The study of drawdowns and drawups has so far been concentrated on their uni- variate characteristics. Encoding the drawdown information of a time series into a time series of discrete values, Chapter 3 uses entropy measures to analyse the correlation and cross correlations of drawdowns and drawups. The method to encode the drawdown information is explained and applied to daily and hourly EUR/USD and GBP/USD exchange rates from 2001 to 2012. For the daily series, we find evidence of dependence among the largest draws (i.e. 5% and 95% quantiles), but it is not as strong as the correlation between the daily returns of the same pair of FX rates. There is also dependence between lead/lagged values of these draws. Similar and stronger findings were found among the hourly data. We further use transfer entropy to examine the spill over and lead-lag information flow between drawup/drawdown of the two exchange rates. Such information flow is indeed detectable in both daily and hourly data. The amount of information transferred is considerably higher for the hourly than the daily data. Both daily and hourly series show clear evidence of information flowing from EUR/USD to GBP/USD and, slightly stronger, in the reverse direction. Robustness tests, using effective transfer entropy, show that the information measured is not due to noise. Chapter 4 uses state space models of volatility to investigate volatility spill overs between exchange rates. Our use of entropy related measures in the investigation of dependencies of two state space series is novel. A set of five daily exchange rates from emerging and developed economies against the dollar over the period 1999 to 2012 is used. We find that among the currency pairs, the co-movement of EUR/USD and CHF/USD volatility states show the strongest observed relationship. With the use of transfer entropy, we find evidence for information flows between the volatility state series of AUD, CAD and BRL.Chapter 5 uses the entropy of S&P realised volatility in detecting changes of volatility regime in order to re-examine the theme of market volatility timing of hedge funds. A one-factor model is used, conditioned on information about the entropy of market volatility, to measure the dynamic of hedge funds equity exposure. On a cross section of around 2500 hedge funds with a focus on the US equity markets we find that, over the period from 2000 to 2014, hedge funds adjust their exposure dynamically in response to changes in volatility regime. This adds to the literature on the volatility timing behaviour of hedge fund manager, but using entropy as a model independent measure of volatility regime. Finally, chapter 6 summarises and concludes with some suggestions for future research.

Tang Him John. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 76-80). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgment --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.2 / Chapter 1.1.1 --- Linear Time Series --- p.2 / Chapter 1.1.2 --- Mixture Models --- p.3 / Chapter 1.1.3 --- EM algorithm --- p.6 / Chapter 1.1.4 --- Model Selection --- p.6 / Chapter 1.2 --- Main Objectives --- p.7 / Chapter 1.3 --- Outline of this thesis --- p.7 / Chapter 2 --- Finite Gaussian Mixture ARMA-GARCH Model --- p.9 / Chapter 2.1 --- Introduction --- p.9 / Chapter 2.1.1 --- "AR, MA, and ARMA" --- p.10 / Chapter 2.1.2 --- Stationarity --- p.11 / Chapter 2.1.3 --- ARCH and GARCH --- p.12 / Chapter 2.1.4 --- Gaussian mixture --- p.13 / Chapter 2.1.5 --- EM and GEM algorithms --- p.14 / Chapter 2.2 --- Finite Gaussian Mixture ARMA-GARCH Model --- p.16 / Chapter 2.3 --- Estimation of Gaussian mixture ARMA-GARCH model --- p.17 / Chapter 2.3.1 --- Autocorrelation and Stationarity --- p.20 / Chapter 2.3.2 --- Model Selection --- p.24 / Chapter 2.4 --- Experiments: First Step Prediction --- p.26 / Chapter 2.5 --- Chapter Summary --- p.28 / Chapter 2.6 --- Notations and Terminologies --- p.30 / Chapter 2.6.1 --- White Noise Time Series --- p.30 / Chapter 2.6.2 --- Lag Operator --- p.30 / Chapter 2.6.3 --- Covariance Stationarity --- p.31 / Chapter 2.6.4 --- Wold's Theorem --- p.31 / Chapter 2.6.5 --- Multivariate Gaussian Density function --- p.32 / Chapter 3 --- Finite Mixture-of-Expert ARMA-GARCH Model --- p.33 / Chapter 3.1 --- Introduction --- p.33 / Chapter 3.1.1 --- Mixture-of-Expert --- p.34 / Chapter 3.1.2 --- Alternative Mixture-of-Expert --- p.35 / Chapter 3.2 --- ARMA-GARCH Finite Mixture-of-Expert Model --- p.36 / Chapter 3.3 --- Estimation of Mixture-of-Expert ARMA-GARCH Model --- p.37 / Chapter 3.3.1 --- Model Selection --- p.38 / Chapter 3.4 --- Experiments: First Step Prediction --- p.41 / Chapter 3.5 --- Second Step and Third Step Prediction --- p.44 / Chapter 3.5.1 --- Calculating Second Step Prediction --- p.44 / Chapter 3.5.2 --- Calculating Third Step Prediction --- p.45 / Chapter 3.5.3 --- Experiments: Second Step and Third Step Prediction . --- p.46 / Chapter 3.6 --- Comparison with Other Models --- p.50 / Chapter 3.7 --- Chapter Summary --- p.57 / Chapter 4 --- Stable Estimation Algorithms --- p.58 / Chapter 4.1 --- Stable AR(1) estimation algorithm --- p.59 / Chapter 4.2 --- Stable AR(2) Estimation Algorithm --- p.60 / Chapter 4.2.1 --- Real p1 and p2 --- p.61 / Chapter 4.2.2 --- Complex p1 and p2 --- p.61 / Chapter 4.2.3 --- Experiments for AR(2) --- p.63 / Chapter 4.3 --- Experiment with Real Data --- p.64 / Chapter 4.4 --- Chapter Summary --- p.65 / Chapter 5 --- Conclusion --- p.66 / Chapter 5.1 --- Further Research --- p.69 / Chapter A --- Equation Derivation --- p.70 / Chapter A.1 --- First Derivatives for Gaussian Mixture ARMA-GARCH Esti- mation --- p.70 / Chapter A.2 --- First Derivatives for Mixture-of-Expert ARMA-GARCH Esti- mation --- p.71 / Chapter A.3 --- First Derivatives for BYY Harmony Function --- p.72 / Chapter A.4 --- First Derivatives for stable estimation algorithms --- p.73 / Chapter A.4.1 --- AR(1) --- p.74 / Chapter A.4.2 --- AR(2) --- p.74 / Bibliography --- p.80

Tong Ka Yau Dennis. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 77-81). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivations --- p.1 / Chapter 1.2 --- Progress on the Problem --- p.2 / Chapter 1.3 --- Our Contributions --- p.3 / Chapter 1.4 --- Thesis Organization --- p.4 / Chapter 2 --- Background on Retiming --- p.5 / Chapter 2.1 --- Introduction --- p.5 / Chapter 2.2 --- Preliminaries --- p.7 / Chapter 2.3 --- Retiming Problem --- p.9 / Chapter 3 --- Literature Review on Retiming --- p.10 / Chapter 3.1 --- Introduction --- p.10 / Chapter 3.2 --- The First Retiming Paper --- p.11 / Chapter 3.2.1 --- """Retiming Synchronous Circuitry""" --- p.11 / Chapter 3.3 --- Important Extensions of the Basic Retiming Algorithm --- p.14 / Chapter 3.3.1 --- """A Fresh Look at Retiming via Clock Skew Optimization""" --- p.14 / Chapter 3.3.2 --- """An Improved Algorithm for Minimum-Area Retiming""" --- p.16 / Chapter 3.3.3 --- """Efficient Implementation of Retiming""" --- p.17 / Chapter 3.4 --- Retiming in Physical Design Stages --- p.19 / Chapter 3.4.1 --- """Physical Planning with Retiming""" --- p.19 / Chapter 3.4.2 --- """Simultaneous Circuit Partitioning/Clustering with Re- timing for Performance Optimization" --- p.20 / Chapter 3.4.3 --- """Performance Driven Multi-level and Multiway Parti- tioning with Retiming" --- p.22 / Chapter 3.5 --- Retiming with More Sophisticated Timing Models --- p.23 / Chapter 3.5.1 --- """Retiming with Non-zero Clock Skew, Variable Register, and Interconnect Delay""" --- p.23 / Chapter 3.5.2 --- """Placement Driven Retiming with a Coupled Edge Tim- ing Model""" --- p.24 / Chapter 3.6 --- Post-Retiming Register Placement --- p.26 / Chapter 3.6.1 --- """Layout Driven Retiming Using the Coupled Edge Tim- ing Model""" --- p.26 / Chapter 3.6.2 --- """Integrating Logic Retiming and Register Placement""" --- p.27 / Chapter 4 --- Retiming with Gate and Wire Delay [2] --- p.29 / Chapter 4.1 --- Introduction --- p.29 / Chapter 4.2 --- Problem Formulation --- p.30 / Chapter 4.3 --- Optimal Approach [2] --- p.31 / Chapter 4.3.1 --- Original Mathematical Framework for Retiming --- p.31 / Chapter 4.3.2 --- A Modified Optimal Approach --- p.33 / Chapter 4.4 --- Near-Optimal Fast Approach [2] --- p.37 / Chapter 4.4.1 --- Considering Wire Delay Only --- p.38 / Chapter 4.4.2 --- Considering Both Gate and Wire Delay --- p.42 / Chapter 4.4.3 --- Computational Complexity --- p.43 / Chapter 4.4.4 --- Experimental Results --- p.44 / Chapter 4.5 --- Lin's Optimal Approach [23] --- p.47 / Chapter 4.5.1 --- Theoretical Results --- p.47 / Chapter 4.5.2 --- Algorithm Description --- p.51 / Chapter 4.5.3 --- Computational Complexity --- p.52 / Chapter 4.5.4 --- Experimental Results --- p.52 / Chapter 4.6 --- Summary --- p.54 / Chapter 5 --- Register Insertion in Placement [36] --- p.55 / Chapter 5.1 --- Introduction --- p.55 / Chapter 5.2 --- Problem Formulation --- p.57 / Chapter 5.3 --- Placement of Registers After Retiming --- p.60 / Chapter 5.3.1 --- Topology Finding --- p.60 / Chapter 5.3.2 --- Register Placement --- p.69 / Chapter 5.4 --- Experimental Results --- p.71 / Chapter 5.5 --- Summary --- p.74 / Chapter 6 --- Conclusion --- p.75 / Bibliography --- p.77

由於特徵尺寸不斷縮小，集成電路在生產過程中的工藝偏差在運行環境中溫度和電壓等參數的波動以及在使用過程中的老化等效應越來越嚴重，導致芯片的時序行為出現很大的不確定性。多數情況下，芯片的關鍵路徑會不時出現時序錯誤。加入更多的時序餘量不是一種很好的解決方案，因為這種保守的設計方法會抵消工藝進步帶來的性能上的好處。這就為設計一個時序可靠的系統提出了極大的挑戰，其中的一些關鍵問題包括：(一)如何有效地分配有限的功率預算去優化那些正爆炸式增加的關鍵路徑的時序性能；(二)如何產生能夠捕捉準確的最壞情況時延的高品質測試向量；(三)為了能夠取得更好的功耗和性能上的平衡，我們將不得不允許芯片在使用過程中出現一些頻率很低的時序錯誤。隨之而來的問題是如何做到在線的檢錯和糾錯。 / 為了解決上述問題，我們首先發明了一種新的技術用於識別所謂的虛假路徑，該方法使我們能夠發現比傳統方法更多的虛假路徑。當將所提取的虛假路徑集成到靜態時序分析工具里以後，我們可以得到更為準確的時序分析結果，同時也能節省本來用於優化這些路徑的成本。接著，考慮到現有的延時自動向量生成(ATPG) 方法會產生功能模式下無法出現的測試向量，這種向量可能會造成測試過程中在被激活的路徑周圍出現過多(或過少)的電源噪聲(PSN) ，從而導致測試過度或者測試不足情況。為此，我們提出了一種新的偽功能ATPG工具。通過同時考慮功能約束以及電路的物理佈局信息，我們使用類似ATPG 的算法產生狀態跳變使其能最大化已激活的路徑周圍的PSN影響。最後，基於近似電路的原理，我們提出了一種新的在線原位校正技術，即InTimeFix，用於糾正時序錯誤。由於實現近似電路的綜合僅需要簡單的電路結構分析，因此該技術能夠很容易的擴展到大型電路設計上去。 / With technology scaling, integrated circuits (ICs) suffer from increasing process, voltage, and temperature (PVT) variations and aging effects. In most cases, these reliability threats manifest themselves as timing errors on speed-paths (i.e., critical or near-critical paths) of the circuit. Embedding a large design guard band to prevent timing errors to occur is not an attractive solution, since this conservative design methodology diminishes the benefit of technology scaling. This creates several challenges on build a reliable systems, and the key problems include (i) how to optimize circuit’s timing performance with limited power budget for explosively increased potential speed-paths; (ii) how to generate high quality delay test pattern to capture ICs’ accurate worst-case delay; (iii) to have better power and performance tradeoff, we have to accept some infrequent timing errors in circuit’s the usage phase. Therefore, the question is how to achieve online timing error resilience. / To address the above issues, we first develop a novel technique to identify so-called false paths, which facilitate us to find much more false paths than conventional methods. By integrating our identified false paths into static timing analysis tool, we are able to achieve more accurate timing information and also save the cost used to optimize false paths. Then, due to the fact that existing delay automated test pattern generation (ATPG) methods may generate test patterns that are functionally-unreachable, and such patterns may incur excessive (or limited) power supply noise (PSN) on sensitized paths in test mode, thus leading to over-testing or under-testing of the circuits, we propose a novel pseudo-functional ATPG tool. By taking both circuit layout information and functional constrains into account, we use ATPG like algorithm to justify transitions that pose the maximized functional PSN effects on sensitized critical paths. Finally, we propose a novel in-situ correction technique to mask timing errors, namely InTimeFix, by introducing redundant approximation circuit with more timing slack for speed-paths into the design. The synthesis of the approximation circuit relies on simple structural analysis of the original circuit, which is easily scalable to large IC designs. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Yuan, Feng. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 88-100). / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Challenges to Solve Timing Uncertainty Problem --- p.2 / Chapter 1.2 --- Contributions and Thesis Outline --- p.5 / Chapter 2 --- Background --- p.7 / Chapter 2.1 --- Sources of Timing Uncertainty --- p.7 / Chapter 2.1.1 --- Process Variation --- p.7 / Chapter 2.1.2 --- Runtime Environment Fluctuation --- p.9 / Chapter 2.1.3 --- Aging Effect --- p.10 / Chapter 2.2 --- Technical Flow to Solve Timing Uncertainty Problem --- p.10 / Chapter 2.3 --- False Path --- p.12 / Chapter 2.3.1 --- Path Sensitization Criteria --- p.12 / Chapter 2.3.2 --- False Path Aware Timing Analysis --- p.13 / Chapter 2.4 --- Manufacturing Testing --- p.14 / Chapter 2.4.1 --- Functional Testing vs. Structural Testing --- p.14 / Chapter 2.4.2 --- Scan-Based DfT --- p.15 / Chapter 2.4.3 --- Pseudo-Functional Testing --- p.17 / Chapter 2.5 --- Timing Error Tolerance --- p.19 / Chapter 2.5.1 --- Timing Error Detection --- p.19 / Chapter 2.5.2 --- Timing Error Recover --- p.20 / Chapter 3 --- Timing-Independent False Path Identification --- p.23 / Chapter 3.1 --- Introduction --- p.23 / Chapter 3.2 --- Preliminaries and Motivation --- p.26 / Chapter 3.2.1 --- Motivation --- p.27 / Chapter 3.3 --- False Path Examination Considering Illegal States --- p.28 / Chapter 3.3.1 --- Path Sensitization Criterion --- p.28 / Chapter 3.3.2 --- Path-Aware Illegal State Identification --- p.30 / Chapter 3.3.3 --- Proposed Examination Procedure --- p.31 / Chapter 3.4 --- False Path Identification --- p.32 / Chapter 3.4.1 --- Overall Flow --- p.34 / Chapter 3.4.2 --- Static Implication Learning --- p.35 / Chapter 3.4.3 --- Suspicious Node Extraction --- p.36 / Chapter 3.4.4 --- S-Frontier Propagation --- p.37 / Chapter 3.5 --- Experimental Results --- p.38 / Chapter 3.6 --- Conclusion and Future Work --- p.42 / Chapter 4 --- PSN Aware Pseudo-Functional Delay Testing --- p.43 / Chapter 4.1 --- Introduction --- p.43 / Chapter 4.2 --- Preliminaries and Motivation --- p.45 / Chapter 4.2.1 --- Motivation --- p.46 / Chapter 4.3 --- Proposed Methodology --- p.48 / Chapter 4.4 --- Maximizing PSN Effects under Functional Constraints --- p.50 / Chapter 4.4.1 --- Pseudo-Functional Relevant Transitions Generation --- p.51 / Chapter 4.5 --- Experimental Results --- p.59 / Chapter 4.5.1 --- Experimental Setup --- p.59 / Chapter 4.5.2 --- Results and Discussion --- p.60 / Chapter 4.6 --- Conclusion --- p.64 / Chapter 5 --- In-Situ Timing Error Masking in Logic Circuits --- p.65 / Chapter 5.1 --- Introduction --- p.65 / Chapter 5.2 --- Prior Work and Motivation --- p.67 / Chapter 5.3 --- In-Situ Timing Error Masking with Approximate Logic --- p.69 / Chapter 5.3.1 --- Equivalent Circuit Construction with Approximate Logic --- p.70 / Chapter 5.3.2 --- Timing Error Masking with Approximate Logic --- p.72 / Chapter 5.4 --- Cost-Efficient Synthesis for InTimeFix --- p.75 / Chapter 5.4.1 --- Overall Flow --- p.76 / Chapter 5.4.2 --- Prime Critical Segment Extraction --- p.77 / Chapter 5.4.3 --- Prime Critical Segment Merging --- p.79 / Chapter 5.5 --- Experimental Results --- p.81 / Chapter 5.5.1 --- Experimental Setup --- p.81 / Chapter 5.5.2 --- Results and Discussion --- p.82 / Chapter 5.6 --- Conclusion --- p.85 / Chapter 6 --- Conclusion and Future Work --- p.86 / Bibliography --- p.100

Fung Pui Cheong Gabriel. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 88-93). / Abstracts in English and Chinese. / Abstract (English) --- p.i / Abstract (Chinese) --- p.ii / Acknowledgement --- p.iii / Contents --- p.v / List of Figures --- p.ix / List of Tables --- p.x / Chapter Part I --- The Very Beginning --- p.1 / Chapter 1 --- Introduction --- p.2 / Chapter 1.1 --- Contributions --- p.3 / Chapter 1.2 --- Dissertation Organization --- p.4 / Chapter 2 --- Problem Formulation --- p.6 / Chapter 2.1 --- Defining the Prediction Task --- p.6 / Chapter 2.2 --- Overview of the System Architecture --- p.8 / Chapter Part II --- Literatures Review --- p.11 / Chapter 3 --- The Social Dynamics of Financial Markets --- p.12 / Chapter 3.1 --- The Collective Behavior of Groups --- p.13 / Chapter 3.2 --- Prediction Based on Publicity Information --- p.16 / Chapter 4 --- Time Series Representation --- p.20 / Chapter 4.1 --- Technical Analysis --- p.20 / Chapter 4.2 --- Piecewise Linear Approximation --- p.23 / Chapter 5 --- Text Classification --- p.27 / Chapter 5.1 --- Document Representation --- p.28 / Chapter 5.2 --- Document Pre-processing --- p.30 / Chapter 5.3 --- Classifier Construction --- p.31 / Chapter 5.3.1 --- Naive Bayes (NB) --- p.31 / Chapter 5.3.2 --- Support Vectors Machine (SVM) --- p.33 / Chapter Part III --- Mining Financial Time Series and Textual Doc- uments Concurrently --- p.36 / Chapter 6 --- Time Series Representation --- p.37 / Chapter 6.1 --- Discovering Trends on the Time Series --- p.37 / Chapter 6.2 --- t-test Based Split and Merge Segmentation Algorithm ´ؤ Splitting Phrase --- p.39 / Chapter 6.3 --- t-test Based Split and Merge Segmentation Algorithm - Merging Phrase --- p.41 / Chapter 7 --- Article Alignment and Pre-processing --- p.43 / Chapter 7.1 --- Aligning News Articles to the Stock Trends --- p.44 / Chapter 7.2 --- Selecting Positive Training Examples --- p.46 / Chapter 7.3 --- Selecting Negative Training Examples --- p.48 / Chapter 8 --- System Learning --- p.52 / Chapter 8.1 --- Similarity Based Classification Approach --- p.53 / Chapter 8.2 --- Category Sketch Generation --- p.55 / Chapter 8.2.1 --- Within-Category Coefficient --- p.55 / Chapter 8.2.2 --- Cross-Category Coefficient --- p.56 / Chapter 8.2.3 --- Average-Importance Coefficient --- p.57 / Chapter 8.3 --- Document Sketch Generation --- p.58 / Chapter 9 --- System Operation --- p.60 / Chapter 9.1 --- System Operation --- p.60 / Chapter Part IV --- Results and Discussions --- p.62 / Chapter 10 --- Evaluations --- p.63 / Chapter 10.1 --- Time Series Evaluations --- p.64 / Chapter 10.2 --- Classifier Evaluations --- p.64 / Chapter 10.2.1 --- Batch Classification Evaluation --- p.69 / Chapter 10.2.2 --- Online Classification Evaluation --- p.71 / Chapter 10.2.3 --- Components Analysis --- p.74 / Chapter 10.2.4 --- Document Sketch Analysis --- p.75 / Chapter 10.3 --- Prediction Evaluations --- p.75 / Chapter 10.3.1 --- Simulation Results --- p.77 / Chapter 10.3.2 --- Hit Rate Analysis --- p.78 / Chapter Part V --- The Final Words --- p.80 / Chapter 11 --- Conclusion and Future Work --- p.81 / Appendix --- p.84 / Chapter A --- Hong Kong Stocks Categorization Powered by Reuters --- p.84 / Chapter B --- Morgan Stanley Capital International (MSCI) Classification --- p.85 / Chapter C --- "Precision, Recall and F1 measure" --- p.86 / Bibliography --- p.88

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O presente trabalho teve como objetivo principal a avaliação do eventual comportamento sazonal dos volumes e preços praticados na floricultura paulista. Para tal, houve a necessidade de seleção dos produtos e entrepostos a serem trabalhados. Os produtos escolhidos foram: rosa, crisântemo e violeta. Dados referentes à década de 90 foram levantados em entrepostos de comercialização selecionados no Estado de São Paulo: CEAGESP-SP (Companhia de Entrepostos e Armazéns Gerais de São Paulo), Veiling Holambra (cooperativa que comercializa produto de produtores via leilão eletrônico) e a CEASA-Campinas (Central de Abastecimento S.A de Campinas). Além desse objetivo principal, realizou-se a identificação dos períodos sazonais existentes, a identificação das características do comportamento sazonal de volumes e preços e a comparação das características de mercado das principais flores e plantas ornamentais comercializadas nos entrepostos selecionados no Estado de São Paulo. Os resultados do trabalho apontaram períodos diferentes para o volume de rosa, crisântemos e violetas. Por outro lado, para cada tipo de flor, observou-se maiores semelhanças para o período de preços praticados nestes entrepostos. Por exemplo, o período 12 foi encontrado para os preços praticados para rosas nos três entrepostos, isto é, existem picos de preços de 12 em 12 meses em cada um deles. Observou-se também grandes ligações entre as datas festivas e os períodos encontrados, tanto para volumes quanto para preços. Portanto, tal como para a maior parte dos produtos agrícolas, informações a respeito do período sazonal também são de extrema importância ao sistema de comercialização de flores e plantas ornamentais. Tanto produtores como consumidores podem se beneficiar a partir do conhecimento do comportamento mais sistemático que seus produtos de interesse revelam. Conhecendo os picos sazonais de comercialização, o produtor pode organizar sua produção de tal forma que novas oportunidades de negócios sejam configuradas a partir de uma melhor e maior distribuição de picos ao longo do ano. Com um maior número de picos de comercialização durante o ano, a receita anual, além de incrementada, será melhor distribuída ao longo do período. / This dissertation has the main objective to evaluate an eventual seasonal behavior of volumes and price series at floriculture in the state of São Paulo, Brazil. For this reason, a selection of products and trade centers was necessary. The chosen products were: rose, chrysanthemum and violet. Data refering to the decade of 1990 were got from the trade centers selected in the state of São Paulo: CEAGESP-SP -‘ Companhia de Entrepostos e Armazéns Gerais de São Paulo’ - , Veiling Holambra - a cooperative which trades directly from producers through eletronic auction - and CEASA-Campinas - a permanent market of flowers in Campinas. Apart from this principal aim, the identification and characterization of the seasonal period of volumes and prices, and the comparison of market characteristics of main flowers and ornamnetal plants traded in the selected facilities in the state of São Paulo were made. The results of the research pointed distinct periods for the volumes and presented similarity for the price periods. For example, the period of 12 months was found to the price of rose in every trade center. Moreover, it was observed that there are links between comercialdates and the found periods for volumes and prices. Therefore, like for the most agricultural products, it is believed that information about seasonal periods is extremelly important for the trade system of each product. With this knowledge, both, producers and consumers, can benefit themselves. Knowing the seasonal periods, producers can organize their production to make it meet consumers’ demand; consequently, they can create more peaks during the whole year. Increasing the trade peaks, the anual revenue also increases being better distributed during the period.

A pesquisa tem por finalidade avaliar dois modelos econométricos de mudanças de preços, que podem ser utilizados em estratégias de arbitragem estatística, o probit ordenado e o de decomposição, estimando seus parâmetros em quatro pregões de mini contratos de dólar futuro negociados na bolsa de valores brasileira. O estudo da negociação em alta frequência com a utilização de dados de transação a transação revela informações relativas à microestrutura de mercado que o ferramental mais tradicional não é capaz de desvendar. Uma das razões é que modelos tradicionais trabalham com variações de preço como variáveis contínuas, enquanto que ao considerar as variações de preço uma variável contínua e não uma variável discreta, como nos modelos aqui avaliados. Este trabalho acrescenta à literatura sobre microestrutura de mercado ao aplicar os modelos estudados em um ativo distinto daqueles avaliados nos papers originais, voltados ao exame do mercado de ações. Esta pesquisa concluiu que os modelos probit ordenado e de decomposição podem ser utilizados para previsão de mini contratos de dólar futuro e que o modelo de decomposição apresenta parâmetros mais significantes. Também concluiu-se que, no modelo probit ordenado, as variáveis de volume e time duration não se apresentaram relevantes na determinação do preço desse contrato e que a quantidade de defasagens utilizadas nos parâmetros estimados pode variar dentre os pregões. / The research aims to evaluate two econometric models of price change, which can be used in strategies of statistical arbitrage, the ordered probit model and the decomposition model, estimating its parameters in four trading sessions of mini US dollar futures contracts traded on the Brazilian Stock Exchange. The study of high frequency trading with the use of trade-by-trade price movements reveals information related to the market microstructure that the more traditional econometric tools are not able to solve when considering the price changes as a continuous variable and not a discrete one, like in the models evaluated here. This work adds to the literature on market microstructure by applying the models studied in an asset different from those evaluated in the original papers, aimed at examining the stock market. This research concluded that the ordered probit and decomposition models can be used to predict mini US dollar futures price changes and that the decomposition model presents more significant parameters. It was also concluded that, in the ordered probit model, the volume and time duration variables were not relevant in determining the price of this contract and that the number of lags used to estimate parameters can vary among the trading sessions.

Neste trabalho foi explorada a aplicação de redes neurais recorrentes simples, também conhecidas como Redes de Elman, na previsão de três séries temporais mensais do varejo de bens e serviços no Brasil. As variáveis destas séries estão relacionadas com a demanda de produtos farmacêuticos, adubos, e tráfego aéreo. As previsões com Redes de Elman foram comparadas com as realizadas por modelos lineares sazonais obtidos através da metodologia de Box-Jenkins. / In this work we explored the application of simple recurrent neural networks, also known as Elman networks, in the prediction of three series of retail goods and services in Brazil. The series are formed by variables related to the monthly demand for pharmaceuticals, fertilizers and domestic air traffic. The forecast with Elman networks were compared with those performed by seasonal linear models obtained by Box-Jenkins methodology.

Neste texto são revisados métodos de reamostragem de séries temporais discretas baseados em wavelets, como alternativas as abordagens clássicas, feitas nos domínios do tempo e da frequência. Tais métodos, conhecidos na literatura como wavestrap e wavestrapping fazem uso, respectivamente, das transformadas wavelet discreta (DWT) e wavelet packet discreta (DWPT). Existem poucos resultados sobre a aplicação da DWPT, de forma que este texto pode ser considerado uma contribuição. Aqui mostra-se também, a superioridade do wavestrapping sobre o wavestrap quando aplicados na estimação da densidade espectral de potência de séries temporais sintéticas geradas a partir de modelos autoregressivos. Tais séries possuem uma particularidade interessante que são picos, geralmente acentuados, em sua reapresentação espectral, de tal forma que grande parte dos métodos clássicos de reamostragem apresentam resultados viesados quando aplicados a estes casos. / This paper reviews resampling methods based on wavelets as an alternative to the classic approaches which are, made in the time and frequency domains. These methods, known in the literature as wavestrap and wavestrapping, make use, respectively, of the discrete wavelet transform (DWT) and of the discrete wavelet packet transform (DWPT). Since only few results are avaliable when the DWPT is applied, this text can be considered a contribution to the subject. Here we, also show the superiority of wavestrapping over wavestrap when they are applied to the estimation of power spectral densities of the synthetic time series generated from autoregressive models. These series have an interesting feature that are sharp peaks in their spectral representation, so that most of the traditional methods of resampling lead to biased results.