Ng, Shou Zhong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 71-77). / Abstracts in English and Chinese. / ABSTRACT --- p.ii / ACKNOWLEDGEMENTS --- p.iv / LIST OF ILLUSTRATIONS --- p.vii / LIST OF TABLES --- p.viii / Chapter 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- MOTIVATIONS / Chapter 1.2 --- OBJECTIVES / Chapter 2 --- LITERATURE REVIEW --- p.12 / Chapter 3 --- DATA DESCRIPTION --- p.22 / Chapter 4 --- METHODOLOGY --- p.25 / Chapter 4.1 --- Cross-Section Dispersion of Per Capita Real Income / Chapter 4.2 --- Stochastic Convergence of the 17 OECD Countries / Chapter 4.3 --- Time-Varying Parameters Model on Convergence / Chapter 4.4 --- Unobserved Components Structural Time Series Models on Converging Economy / Chapter 5 --- ESTIMATION RESULTS --- p.40 / Chapter 5.1 --- Cross-Section Dispersion of Per Capita Real Income / Chapter 5.2 --- Stochastic Convergence of the 17 OECD Countries / Chapter 5.3 --- Time-Varying Parameters Model on Convergence / Chapter 5.4 --- Unobserved Components Structural Time Series Models on Converging Economy / Chapter 6 --- CONCLUSIONS --- p.64 / APPENDICES --- p.67 / BIBLIOGRAPHY --- p.71 / ILLUSTRATIONS --- p.78 / TABLES --- p.87

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.

<p>The subject of this dissertation encompasses a comprehensive overview<br />and analysis of the impact of Sakoe-Chiba global constraint on the most<br />commonly used elastic similarity measures in the field of time-series data<br />mining with a focus on classification accuracy. The choice of similarity<br />measure is one of the most significant aspects of time-series analysis&nbsp; -&nbsp; it<br />should correctly reflect the resemblance between the data presented in<br />the form of time series. Similarity measures represent a critical<br />component of many tasks of mining time series, including: classification,<br />clustering, prediction, anomaly detection, and others.</p><p>The research covered by this dissertation is oriented on several issues:</p><p>1.&nbsp; review of the effects of&nbsp; global constraints on the<br />performance of computing similarity measures,</p><p>2.&nbsp; a detailed analysis of the influence of constraining the elastic<br />similarity measures on the accuracy of classical classification<br />techniques,</p><p>3.&nbsp; an extensive study of the impact of different weighting<br />schemes on the classification of time series,</p><p>4.&nbsp; development of an open source library that integrates the<br />main techniques and methods required for analysis and<br />mining time series, and which is used for the realization of<br />these experiments</p> / <p>Predmet istraživanja ove disertacije obuhvata detaljan pregled i analizu uticaja Sakoe-Chiba globalnog ograničenja na najče&scaron;će kori&scaron;ćene elastične mere sličnosti u oblasti data mining-a vremenskih serija sa naglaskom na tačnost klasifikacije. Izbor mere sličnosti jedan je od najvažnijih aspekata analize vremenskih serija&nbsp; -&nbsp; ona treba&nbsp; verno reflektovati sličnost između podataka prikazanih u obliku vremenskih serija.&nbsp; Mera sličnosti predstavlјa kritičnu komponentu mnogih zadataka&nbsp; mining-a vremenskih serija, uklјučujući klasifikaciju, grupisanje (eng.&nbsp; clustering), predviđanje,&nbsp;otkrivanje anomalija i drugih.</p><p>Istraživanje obuhvaćeno ovom disertacijom usmereno je na nekoliko pravaca:</p><p>1.&nbsp; pregled efekata globalnih ograničenja na performanse računanja mera sličnosti,</p><p>2.&nbsp; detalјna analiza posledice ograničenja elastičnih mera sličnosti na tačnost klasifikacije klasičnih tehnika klasifikacije,</p><p>3.&nbsp; opsežna studija uticaj različitih načina računanja težina (eng. weighting scheme) na klasifikaciju vremenskih serija,</p><p>4.&nbsp; razvoj biblioteke otvorenog koda (Framework for Analysis and Prediction&nbsp; -&nbsp; FAP) koja će integrisati glavne tehnike i metode potrebne za analizu i mining&nbsp; vremenskih serija i koja je kori&scaron;ćena za realizaciju ovih eksperimenata.</p> / <p>Predmet istraživanja ove disertacije obuhvata detaljan pregled i analizu uticaja Sakoe-Chiba globalnog ograničenja na najče&scaron;će kori&scaron;ćene elastične mere sličnosti u oblasti data mining-a vremenskih serija sa naglaskom na tačnost klasifikacije. Izbor mere sličnosti jedan je od najvažnijih aspekata analize vremenskih serija&nbsp; -&nbsp; ona treba&nbsp; verno reflektovati sličnost između podataka prikazanih u obliku vremenskih serija.&nbsp; Mera sličnosti predstavlja kritičnu komponentu mnogih zadataka&nbsp; mining-a vremenskih serija, uključujući klasifikaciju, grupisanje (eng.&nbsp; clustering), predviđanje,&nbsp;otkrivanje anomalija i drugih.</p><p>Istraživanje obuhvaćeno ovom disertacijom usmereno je na nekoliko pravaca:</p><p>1.&nbsp; pregled efekata globalnih ograničenja na performanse računanja mera sličnosti,</p><p>2.&nbsp; detaljna analiza posledice ograničenja elastičnih mera sličnosti na tačnost klasifikacije klasičnih tehnika klasifikacije,</p><p>3.&nbsp; opsežna studija uticaj različitih načina računanja težina (eng. weighting scheme) na klasifikaciju vremenskih serija,</p><p>4.&nbsp; razvoj biblioteke otvorenog koda (Framework for Analysis and Prediction&nbsp; -&nbsp; FAP) koja će integrisati glavne tehnike i metode potrebne za analizu i mining&nbsp; vremenskih serija i koja je kori&scaron;ćena za realizaciju ovih eksperimenata.</p>

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.

As we continue to produce large amounts of time-series data, the need for data analysis is growing rapidly to help gain insights from this data. These insights form the foundation of data-driven decisions in various aspects of life. Data annotations are information about the data such as comments, errors and provenance, which provide context to the underlying data and aid in meaningful data analysis in domains such as scientific research, genomics and ECG analysis. Storing such annotations in the database along with the data makes them available to help with analysis of the data. In this thesis, I propose a user-friendly technique for Annotation-Enabled Analysis through which a user can employ annotations to help query and analyze data without having prior knowledge of the details of the database schema or any kind of database programming language. The proposed technique receives the request for analysis as a high-level specification, hiding the details of the schema, joins, etc., and parses it, validates the input and converts it into SQL. This SQL query can then be executed in a relational database and the result of the query returned to the user. I evaluate this technique by providing real-world data from a building-data platform containing data about Portland State University buildings such as room temperature, air volume and CO2 level. This data is annotated with information such as class schedules, power outages and control modes (for example, day or night mode). I test my technique with three increasingly sophisticated levels of use cases drawn from this building science domain. (1) Retrieve data with include or exclude annotation selection (2) Correlate data with include or exclude annotation selection (3) Align data based on include annotation selection to support aggregation over multiple periods. I evaluate the technique by performing two kinds of tests: (1) To validate correctness, I generate synthetic datasets for which I know the expected result of these annotation-enabled analyses and compare the expected results with the results generated from my technique (2) I evaluate the performance of the queries generated by this service with respect to execution time in the database by comparing them with alternative SQL translations that I developed.

What consequences arise as a result of repeated control of the legislature by the same party or coalition? Are incumbent parties less likely to lose an election the longer they remain in power? Furthermore, as parties remain in power longer and longer, do the factors which electoral scholars have proposed influence elections have less of an impact on election outcomes? The purpose of this project is to examine the electoral impact of repeated control of the legislature by the same party or ruling coalition. In this project, I argue that the length of time an incumbent party or coalition has maintained control of the legislature is a critical consideration for scholars interested in studying elections. In doing so, I hope to develop a better understanding of elections, the factors which influence election, and the mechanisms by which these factors affect election outcomes. Central to this project is the phenomenon I call party duration. I define party duration as the number of years the incumbent party has maintained control of the legislature in unicameral legislatures or the lower house in bicameral legislatures. This is the party that has secured enough seats to control the legislature independently in cases where a single party controls the legislature, or the party that serves as the largest party in the ruling coalition that controls the legislature in cases where a single party does not control the legislature by itself. Using cross-sectional time-series analysis to study a novel dataset, I show that not only does increasing party duration decreases the likelihood that an incumbent party will lose an election, controlling for various other factors, but I find evidence that party duration also affects the effect of other variables which influence elections. Specifically, I focus on the impact that the length of party duration has on the effect of economic conditions on the incumbent party's performance in elections. These findings highlight the importance of party duration, a variable which has previously not received attention from electoral scholars

Phreatic overgrowths on speleothems (POS) are one of many sea-level proxies available to Quaternary geologists in Mallorca; these carbonate encrustations form at the air-water interface in cave passages flooded with brackish water. POS are ideal for reconstruction of western Mediterranean sea level because they are widespread in Mallorca's caves, can be precisely dated by U-series methods, constrain sea-level stands to sub-meter elevation, and are well preserved and accessible in the subterranean environment. This research investigates the POS depositional environment, which is relatively understudied compared to the other proxies used for sea-level reconstructions. This disparity has led to assumptions on many aspects of the POS precipitation. Further, POS are typically composed of calcite, but sometimes the metastable polymorph aragonite is present instead. Two caves were studied because of the presence of a modern POS horizon of aragonite and calcite: Cova des Pas de Vallgornera (Vallgornera) and Coves del Drac (Drac), respectively. High-resolution air and water physical parameters were collected for the first time, along with monthly water samples for stable isotope and elemental analysis. This 16-month record was supplemented with detailed geochemical studies throughout the project, including water-column profiles and CO2 sampling campaigns. The water level in both caves preserves the semi-diurnal Mediterranean Sea tide signal, with a lag of approximately four hours. The fluctuation in both caves is slightly attenuated, and the direct effects of barometric pressure and precipitation could not be discerned from the primary control of tidal pumping. Calculations based on salinity and isotope analysis show that less than 20% of the solution in each cave is seawater. Degassing of CO2 from the cave water to air was documented at both locations, with sporadic calcium carbonate supersaturation. These conditions are strongly dependent on annual cave ventilation, which becomes active during winter when cold, dense tropospheric air sinks into the subsurface. In addition to seasonal thermo-circulation, fluctuating water level displaces cave air and likely initiates tropospheric exchange throughout the year. This process primarily occurs through fissures in thin overlying bedrock at Vallgornera and through the large entrance in Drac. Higher elemental ratios (Mg:Ca, Sr:Ca, Mg:Sr) known to enhance aragonite precipitation or inhibit calcite precipitation were recorded in Vallgornera's water. A linear correlation with salinity was not observed, so higher ratios in Vallgornera must be contributed from differences in lithology, bedrock weathering intensity, or nearby rising thermal waters. In summary, this research confirms POS strengths as sea-level proxies from geochemical and hydrological perspectives. These carbonate encrustations are precipitated at the air-water interface, which fluctuates as an attenuated expression of Mediterranean Sea tide. Degassing of CO2 from the cave water to air, which promotes calcium carbonate supersaturation, is the major control on POS deposition, and is facilitated by winter ventilation and likely water-level fluctuations. CO2 degassing (and theoretically precipitation of POS) in isotopic equilibrium is possible in caves with restricted ventilation (small/sealed entrances, small passages). Aragonite may be precipitated instead of calcite because of local modifications to the geochemical system from bedrock weathering or contributions from deep groundwater.

This study focuses on how the construction of a paleoclimate time series influences the interpretation in the frequency domain. Three time series are examined: a New Caledonian coral (Amedee Island), a Chinese speleothem (Dongge Cave), and New Mexican trees (El Malpais). This study presents a monthly resolved coral Sr/Ca time series from New Caledonia that reconstructs sea surface temperature (SST; 1648-1999). The chronology is based on density-band counting, cross-correlating Sr/Ca, and ²³°Th dating. The intracolony coral Sr/Ca variations are coherent on interannual to centennial time scales and are reproducible for >300 years. The SST reconstruction reveals estimated cooling trend (~0.4°C) from 1741-1815, a colder nineteenth century (~0.6°C), and a warming trend (~0.6°C) in the twentieth century. Spectral and wavelet analysis reveals significant inter-decadal periodicities (~14-21 years/cycle) that modulate with time, and nearly persistent multi-decadal periodicities (~25-33 years/cycle) that do not exhibit coherence with the Inter-decadal Pacific Oscillation. The multi-decadal periodicities may be a harmonic of the inter-decadal periodicities or may represent an independent mode not previously recognized. The Dongge Cave time series is based on uneven time intervals between data points (∆t) requiring interpolation to a constant ∆t for analysis with traditional spectral methods. A comparison of the even and uneven ∆t spectra using the Lomb-Scargle transform reveals the interpolated spectrum contains suppressed periodicities (<20 years/cycle), in contrast to the uninterpolated spectrum, resulting in a steeper slope in the red noise model thus influencing significance testing. The El Malpais time series is an average of tree-ring width series. Spectral analysis of the entire time series identified significant periodicities. However, significance varies between three temporal subsets, in which the number of series varies; therefore, these periodicities may be a function of the number of series or may represent a real temporal variability. Cross-spectral analysis of the El Malpais and Dongge Cave time series reveals significant coherence; however, cross-wavelet analysis, which examines localized frequencies in the time domain, reveals a lack of correlation; therefore, coherence in the frequency domain does not indicate correlation in the time domain.

Abstract not available

This thesis presents the results of research into the use of factor models for stationary economic time series. Two basic scenarios are considered. The first is a situation where a large number of observations are available on a relatively small number variables, and a dynamic factor model is specified. It is shown that a dynamic factor model may be derived as a representation of a VARMA model of reduced spectral rank observed subject to measurement error. In some cases the resulting factor model corresponds to a minimal state-space representation of the VARMA plus noise model. Identification is discussed and proved for a fairly general class of dynamic factor model, and a frequency domain estimation procedure is proposed which has the advantage of generalising easily to models with rich dynamic structures. The second scenario is one where both the number of variables and the number of observations jointly diverge to infinity. The principal components estimator is considered in this case, and consistency is proved under assumptions which allow for much more error cross-correlation than the previously published theorems. Ancillary results include finite sample/variables bounds linking population principal components to population factors, and consistency results for principal components in a dual limit framework under a `gap' condition on the eigenvalues. A new factor model, named the Grouped Variable Approximate Factor Model, is introduced. This factor model allows for arbitrarily strong correlation between some of the errors, provided that the variables corresponding to the strongly correlated errors may be arranged into groups. An approximate instrumental variables estimator is proposed for the model and consistency is proved.