Volatility modeling based on GARCH-skewed-t-type models for Chinese stock market

As an emerging stock market with enormous potential, Chinese stock market has apparent volatility clustering appearance along with typical feature of leptokurtic, negative skewness and fat tail in its index yield series. The model based on traditional normal distribution often underestimate the risk, which would lead to profound loss for the investors and financial institution when the extreme events happened. VaR(Value at Risk), which measures risk as a certain value, is widely used in financial industry for its intuitive and concise characteristics. Since parameter method of the VaR calculation is the mostly implementation in practice, the choice of appropriate probability distribution function and variance can quite improve its accuracy. Therefore, the conditional variance is estimated by GARCH-type models and the assumption of normal distribution is replaced by skewed-t distribution. Compared with the common RiskMetrics based on normal distribution, the ARMA-GJR-GARCH-skewed-t model has better adaptability and precision for the VaR estimation of indices of Chinese stock markets.Como um mercado emergente de ações com enorme potencial, o mercado acionário chinês tem uma aparente aparência de agregação de volatilidade, juntamente com uma característica típica de leptocurtice, assimetria negativa e cauda gorda em sua série de índices de rendimento. O modelo baseado na distribuição normal tradicional freqüentemente subestima o risco, o que levaria a perdas profundas para os investidores e instituições financeiras quando os eventos extremos acontecessem. O VaR (Value at Risk), que mede o risco como um determinado valor, é amplamente utilizado no setor financeiro por suas características intuitivas e concisas. Como o método de parâmetro do cálculo do VaR é a maior parte da implementação na prática, a escolha da função de distribuição de probabilidade apropriada e da variância pode melhorar bastante sua precisão. Portanto, a variância condicional é estimada pelo modelo GARCH-types e a suposição de distribuição normal é substituída pela distribuição skewed-t. Comparado com o comum RiskMetrics baseado na distribuição normal e outros modelos do tipo GARCHskewed- t, o modelo ARMA-GJR-GARCH-skewed-t tem melhor adaptabilidade e precisão para a estimativa de VaR de índices dos mercados de ações chineses

Uncertain voronoi cell computation based on space decomposition

LNCS v. 9239 entitled: Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015 ... ProceedingsThe problem of computing Voronoi cells for spatial objects whose locations are not certain has been recently studied. In this work, we propose a new approach to compute Voronoi cells for the case of objects having rectangular uncertainty regions. Since exact computation of Voronoi cells is hard, we propose an approximate solution. The main idea of this solution is to apply hierarchical access methods for both data and object space. Our space index is used to efficiently find spatial regions which must (not) be inside a Voronoi cell. Our object index is used to efficiently identify Delauny relations, i.e., data objects which affect the shape of a Voronoi cell. We develop three algorithms to explore index structures and show that the approach that descends both index structures in parallel yields fast query processing times. Our experiments show that we are able to approximate uncertain Voronoi cells much more effectively than the state-of-the-art, and at the same time, improve run-time performance.postprin

Towards Mobility Data Science (Vision Paper)

Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ubiquitously. In recent years, the use of mobility data has demonstrated significant impact in various domains including traffic management, urban planning, and health sciences. In this paper, we present the emerging domain of mobility data science. Towards a unified approach to mobility data science, we envision a pipeline having the following components: mobility data collection, cleaning, analysis, management, and privacy. For each of these components, we explain how mobility data science differs from general data science, we survey the current state of the art and describe open challenges for the research community in the coming years.Comment: Updated arXiv metadata to include two authors that were missing from the metadata. PDF has not been change

Efficient point-based trajectory search

LNCS v. 9239 entitled: Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. ProceedingsTrajectory data capture the traveling history of moving objects such as people or vehicles. With the proliferation of GPS and tracking technology, huge volumes of trajectories are rapidly generated and collected. Under this, applications such as route recommendation and traveling behavior mining call for efficient trajectory retrieval. In this paper, we first focus on distance-based trajectory search; given a collection of trajectories and a set query points, the goal is to retrieve the top-k trajectories that pass as close as possible to all query points. We advance the state-of-the-art by combining existing approaches to a hybrid method and also proposing an alternative, more efficient rangebased approach. Second, we propose and study the practical variant of bounded distance-based search, which takes into account the temporal characteristics of the searched trajectories. Through an extensive experimental analysis with real trajectory data, we show that our rangebased approach outperforms previous methods by at least one order of magnitude. © Springer International Publishing Switzerland 2015.postprin

Design Methodology for Six-Port Equal/Unequal Quadrature and Rat-Race Couplers With Balanced and Unbalanced Ports Terminated by Arbitrary Resistances

For the first time, the 6-port quadrature and rat-race couplers with balanced-unbalanced-hybrid ports are proposed. The corresponding design methodology is presented, which is capable of designing the proposed couplers with arbitrary power divisions and terminated resistances. In this paper, four types including quadrature and rat-race couplers are fully analyzed, covering all the application configurations of the balanced/unbalanced ports. Besides, the design equations are rigorously derived, with the final design procedures presented. Eventually, prototypes of the four coupler types are fabricated and experimentally measured. The final results sufficiently validate the proposed methodology

RESEARCH TRENDS ON COMMUNITY-BASED TOURISM IN THE PERIOD 2013 - 2023

Community-based tourism (CBT) has been around since the 1970s and so far, has grown in popularity in most continents. This study systematically evaluates and generalizes theoretical and practical issues on CBT based on 87 related articles published in scientific journals under the Scopus system from 2013 to 2023 through the application of content analysis methods. The results also show that research in this area has different research areas and mainly uses qualitative methods. The literature review identified a number of key themes including: (1) benefits of CBT development, (2) community and stakeholder engagement, (3) advantages and barriers in CBT development, (4) community perceptions about CBT, and (5) sustainable CBT development. The article has analyzed research trends on CBT: theory and application.  Article visualizations