Analysis of contagion from the constant conditional correlation model with Markov regime switching

Over the last decades, the analysis of the transmissions of international nancial events has become the subject of many academic studies focused on multivariate volatility models volatility. The goal of this study is to evaluate the nancial contagion between stock market returns. The econometric approach employed was originally presented by Pelletier (2006), named Regime Switching Dynamic Correlation (RSDC). This methodology involves the combination of Constant Conditional Correlation Model (CCC) proposed by Bollerslev (1990) with Markov Regime Switching Model suggested by Hamilton and Susmel (1994). A modi cation was made in the original RSDC model, the introduction of the GJR-GARCH model formulated in Glosten, Jagannathan e Runkle (1993), on the equation of the conditional univariate variances to allow asymmetric e ects in volatility be captured. The database was built with the series of daily closing stock market indices in the United States (SP500), United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) for the period from 02/01/2003 to 09/20/2012. Throughout the work the methodology was compared with others most widespread in the literature, and the model RSDC with two regimes was de ned as the most appropriate for the selected sample. The set of results provide evidence for the existence of nancial contagion between markets of the four countries considering the de nition of nancial contagion from the World Bank called very restrictive. Such a conclusion should be evaluated carefully considering the wide diversity of de nitions of contagion in the literature.

Brazil and Turkey, a comparative analysis of both countries' economic development and institutional design from the Great Depression to the early 21st century

Apos uma década de rápido crescimento econômico na primeira década do século 21, Brasil e Turquia foram considerados duas das economias emergentes mais dinâmicas e promissoras. No entanto, vários sinais de dificuldades econômicas e tensões políticas reapareceram recentemente e simultaneamente nos dois países. Acreditamos que esses sinais e a sua simultaneidade podem ser entendidos melhor com um olhar retrospectivo sobre a história econômica dos dois países, que revela ser surpreendentemente paralela. Numa primeira parte, empreendemos uma comparação abrangente da história econômica brasileira e turca para mostrar as numerosas similaridades entre os desafios de política econômica que os dois países enfrentaram, assim como entre as respostas que eles lhes deram desde a virada da Grande Depressão até a primeira década do século 21. Essas escolhas de política econômica comuns dão forma a uma trajetória de desenvolvimento notavelmente análoga, caracterizada primeiro pela adoção do modelo de industrialização por substituição das importações (ISI) no contexto da recessão mundial dos anos 1930; depois pela intensificação e crise final desse modelo nos anos 1980; e finalmente por duas décadas de estabilização e transição para um modelo econômico mais liberal. Numa segunda parte, o desenvolvimento das instituições econômicas e políticas, assim como da economia política subjacente nos dois países, são analisados comparativamente a fim de prover alguns elementos de explicação do paralelo observado na primeira parte. Sustentamos que o marco institucional estabelecido nos dois países durante esse período também têm varias características fundamentais em comum e contribui a explicar as escolhas de política econômica e as performances econômicas comparáveis, detalhadas na primeira parte. Este estudo aborda elementos do contexto histórico úteis para compreender a situação econômica e política atual nos dois países. Potencialmente também constitui uma tentativa de considerar as economias emergentes numa perspectiva histórica e comparativa mais ampla para entender melhor as suas fraquezas institucionais e adotar um olhar mais equilibrado sobre seu potencial econômico.

Exploring different social media users from the millennials’ generation: a cross-cultural behavioral analysis of brazilian users of Facebook and chinese users of RenRen

With the increasing importance of digital communication and its distinct characteristics, marketing tools and strategies adopted by companies have changed dramatically. Among the many digital marketing tools and new media channels available for marketers, the phenomenon known as social media is one of the most complex and enigmatic. It has a range that still is quite unexplored and deeply transforms the present view on the promotion mix (Mangold & Faulds, 2009). Conversations among users on social media directly affect their perceptions on products, services and brands. But more than that, a wide range of other subjects can also become topics of conversations on social media. Hit songs, sporting events, celebrity news and even natural disasters and politics are topics that often become viral on the web. Thus, companies must grasp that, and in order to become more interesting and relevant, they must take part in these conversations inserting their brands in these online dynamic dialogues. This paper focuses on how these social interactions are manifested in the web in to two distinct cultures, Brazil and China. By understanding the similarities and differences of these cultures, this study helps firms to better adjust its marketing efforts across regions, targeting and positioning themselves, not only geographically and culturally, but also across different web platforms (Facebook and RenRen). By examining how companies should focus their efforts according to each segment in social media, firms can also maximize its results in communication and mitigate risks. The findings suggest that differences in cultural dimensions in these two countries directly affect their virtual social networking behavior in many dimensions (Identity, Presence, Relationships, Reputation, Groups, Conversations and Sharing). Accordingly, marketing efforts must be tailored to each comportment and expectations.

Convergence analysis of sampling-based decomposition methods for risk-averse multistage stochastic convex programs

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.

Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.

Volatile flavour constituent patterns of terras madeirenses red wines extracted by dynamic headspace solid‐phase microextraction

A suitable analytical procedure based on static headspace solid-phase microextraction (SPME) followed by thermal desorption gas chromatography–ion trap mass spectrometry detection (GC–ITDMS), was developed and applied for the qualitative and semi-quantitative analysis of volatile components of Portuguese Terras Madeirenses red wines. The headspace SPME method was optimised in terms of fibre coating, extraction time, and extraction temperature. The performance of three commercially available SPME fibres, viz. 100 lm polydimethylsiloxane; 85 lm polyacrylate, PA; and 50/30 lm divinylbenzene/carboxen on polydimethylsiloxane, was evaluated and compared. The highest amounts extracted, in terms of the maximum signal recorded for the total volatile composition, were obtained with a PA coating fibre at 308C during an extraction time of 60 min with a constant stirring at 750 rpm, after saturation of the sample with NaCl (30%, w/v). More than sixty volatile compounds, belonging to different biosynthetic pathways, have been identified, including fatty acid ethyl esters, higher alcohols, fatty acids, higher alcohol acetates, isoamyl esters, carbonyl compounds, and monoterpenols/C13-norisoprenoids.

Dynamic headspace solid-phase microextraction combined with one-dimensional gas chromatography–mass spectrometry as a powerful tool to differentiate banana cultivars based on their volatile metabolite profile

In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.

A new and improved strategy combining a dispersive-solid phase extraction-based multiclass method with ultra high pressure liquid chromatography for analysis of low molecular weight polyphenols in vegetables

This paper reports on the development and optimization of a modified Quick, Easy, Cheap Effective, Rugged and Safe (QuEChERS) based extraction technique coupled with a clean-up dispersive-solid phase extraction (dSPE) as a new, reliable and powerful strategy to enhance the extraction efficiency of free low molecular-weight polyphenols in selected species of dietary vegetables. The process involves two simple steps. First, the homogenized samples are extracted and partitioned using an organic solvent and salt solution. Then, the supernatant is further extracted and cleaned using a dSPE technique. Final clear extracts of vegetables were concentrated under vacuum to near dryness and taken up into initial mobile phase (0.1% formic acid and 20% methanol). The separation and quantification of free low molecular weight polyphenols from the vegetable extracts was achieved by ultrahigh pressure liquid chromatography (UHPLC) equipped with a phodiode array (PDA) detection system and a Trifunctional High Strength Silica capillary analytical column (HSS T3), specially designed for polar compounds. The performance of the method was assessed by studying the selectivity, linear dynamic range, the limit of detection (LOD) and limit of quantification (LOQ), precision, trueness, and matrix effects. The validation parameters of the method showed satisfactory figures of merit. Good linearity (View the MathML sourceRvalues2>0.954; (+)-catechin in carrot samples) was achieved at the studied concentration range. Reproducibility was better than 3%. Consistent recoveries of polyphenols ranging from 78.4 to 99.9% were observed when all target vegetable samples were spiked at two concentration levels, with relative standard deviations (RSDs, n = 5) lower than 2.9%. The LODs and the LOQs ranged from 0.005 μg mL−1 (trans-resveratrol, carrot) to 0.62 μg mL−1 (syringic acid, garlic) and from 0.016 μg mL−1 (trans-resveratrol, carrot) to 0.87 μg mL−1 ((+)-catechin, carrot) depending on the compound. The method was applied for studying the occurrence of free low molecular weight polyphenols in eight selected dietary vegetables (broccoli, tomato, carrot, garlic, onion, red pepper, green pepper and beetroot), providing a valuable and promising tool for food quality evaluation.

Dimensional analysis of soil properties after treatment with the rotary paraplow, a new conservationist tillage tool

This study examined a new conservation tillage tool, the rotary paraplow. Emphasis was placed on evaluating the tool's conservation potential using dimensionless graph analysis. The dynamic conditions of the soil were investigated in terms of physical soil properties. Having determined the variables to be measured, dimensional analysis was used to plan the experiments. Two variations were considered for each dependent variable (linear speed, working depth, and rotation velocity), totaling eight treatments, allotting in each an experimental strip with five data collection points. This arrangement totaled 16 experimental strips, with 80 data collection points for all variables. The rotary paraplow generates a trapezoidal furrow for planting with a very wide bottom and narrower at the top. The volumetric subsoiling action generates cracks on the sides of the band. Because of their specific geometry the blades of rotary paraplow generate a soil failure according to its natural crack angle, optimizing the energy use, while preserving the natural soil properties. Results showed the conservation character of the rotary paraplow, capable of breaking up clods for planting without changing the original physical soil properties.

Three-Dimensional Semiautomatic Road Extraction From a High-Resolution Aerial Image by Dynamic-Programming Optimization in the Object Space

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modeling and analysis of artificial neural networks applied in operations research

Artificial neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements. Systems based on artificial neural networks have high computational rates due to the use of a massive number of these computational elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving problems related to operations research. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

Prediction of Soil Properties from the Concepts of Energy Transfer in Dynamic Penetration Tests

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Dynamic mechanical properties for polyurethane elastomers applied in elastomeric mortar

Dynamic mechanical properties of a polyurethane (PU) elastomer and a mortar processed with the same elastomer (modified polytetramethylene ether glycol (PTMEG)) were studied. The results obtained showed that the liquid aromatic amine ETHACURE (R) 300, used as cure agent, can be used to substitute the aromatic amine MOCA (R), which is usually used as cure agent in high performance elastomers. The resulting mortar produced with ETHACURE (R) 300 presents similar dynamic-mechanical thermal properties when compared with MOCA (R). However, dynamic-mechanical thermal analysis studies showed that the mortar developed with ETHACURE (R) 300 presents some advantages such as the low values of tan d, indicating a good capacity of recovery of the strain after retreating an applied force. (c) 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

Sensitivity analysis for transient stability studies

The paper presents a method for security control of electric power systems effected by generation reallocation, determined by sensitivity analysis and optimisation. The model is developed considering the dynamic aspects of the network (transient stability). Security control methodology is developed using sensitivity analysis of the security margin in relation to the mechanical power of synchronous machines in the system. The power reallocated to each machine is determined by means of linear programming. To illustrate the proposed methodology, an example is presented which considers a multimachine system composed of 10 synchronous machines, 45 buses, and 72 transmission lines, based on the configuration of a southern Brazilian system.

Stability analysis of power systems described with detailed models by automatic method

The power system stability analysis is approached taking into explicit account the dynamic performance of generators internal voltages and control devices. The proposed method is not a direct method in the usual sense since conclusion for stability or instability is not exclusively based on energy function considerations but it is automatic since the conclusion is achieved without an analyst intervention. The stability test accounts for the nonconservative nature of the system with control devices such as the automatic voltage regulator (AVR) and automatic generation control (AGC) in contrast with the well-known direct methods. An energy function is derived for the system with machines forth-order model, AVR and AGC and it is used to start the analysis procedure and to point out criticalities. The conclusive analysis itself is made by means of a method based on the definition of a region surrounding the equilibrium point where the system net torque is equilibrium restorative. This region is named positive synchronization region (PSR). Since the definition of the PSR boundaries have no dependence on modelling approximation, the PSR test conduces to reliable results. (C) 2008 Elsevier Ltd. All rights reserved.