A Spatial-Temporal Downscaling Approach To Construction Of Rainfall Intensity-Duration-Frequency Relations In The Context Of Climate Change

This paper proposes a spatial-temporal downscaling approach to construction of the intensity-duration-frequency (IDF) relations at a local site in the context of climate change and variability. More specifically, the proposed approach is based on a combination of a spatial downscaling method to link large-scale climate variables given by General Circulation Model (GCM) simulations with daily extreme precipitations at a site and a temporal downscaling procedure to describe the relationships between daily and sub-daily extreme precipitations based on the scaling General Extreme Value (GEV) distribution. The feasibility and accuracy of the suggested method were assessed using rainfall data available at eight stations in Quebec (Canada) for the 1961-2000 period and climate simulations under four different climate change scenarios provided by the Canadian (CGCM3) and UK (HadCM3) GCM models. Results of this application have indicated that it is feasible to link sub-daily extreme rainfalls at a local site with large-scale GCM-based daily climate predictors for the construction of the IDF relations for present (1961-1990) and future (2020s, 2050s, and 2080s) periods at a given site under different climate change scenarios. In addition, it was found that annual maximum rainfalls downscaled from the HadCM3 displayed a smaller change in the future, while those values estimated from the CGCM3 indicated a large increasing trend for future periods. This result has demonstrated the presence of high uncertainty in climate simulations provided by different GCMs. In summary, the proposed spatial-temporal downscaling method provided an essential tool for the estimation of extreme rainfalls that are required for various climate-related impact assessment studies for a given region.

Testing the Markov property with ultra high frequency financial data

This paper develops a framework to test whether discrete-valued irregularly-spaced financial transactions data follow a subordinated Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete level. This framework is convenient for it accommodates not only the irregular spacing of transactions data, but also price discreteness. Further, it turns out that, under such an observation rule, the current price duration is independent of previous price durations given the current price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Finally, we investigate whether or not bid-ask spreads follow Markov processes using transactions data from the New York Stock Exchange. The motivation lies on the fact that asymmetric information models of market microstructures predict that the Markov property does not hold for the bid-ask spread. The results are mixed in the sense that the Markov assumption is rejected for three out of the five stocks we have analyzed.

Modelo da dinâmica de um livro de ordens para aplicações em high-frequency trading

As operações de alta frequência (High-Frequency Trading - HFT) estão crescendo cada vez mais na BOVESPA (Bolsa de Valores de São Paulo), porém seu volume ainda se encontra muito atrás do volume de operações similares realizadas em outras bolsas de relevância internacional. Este trabalho pretende criar oportunidades para futuras aplicações e pesquisas nesta área. Visando aplicações práticas, este trabalho foca na aplicação de um modelo que rege a dinâmica do livro de ordens a dados do mercado brasileiro. Tal modelo é construído com base em informações do próprio livro de ordens, apenas. Depois de construído o modelo, o mesmo é utilizado em uma simulação de uma estratégia de arbitragem estatística de alta frequência. A base de dados utilizada para a realização deste trabalho é constituída pelas ordens lançadas na BOVESPA para a ação PETR4.

Forecasting daily volatility using high frequency financial data

Aiming at empirical findings, this work focuses on applying the HEAVY model for daily volatility with financial data from the Brazilian market. Quite similar to GARCH, this model seeks to harness high frequency data in order to achieve its objectives. Four variations of it were then implemented and their fit compared to GARCH equivalents, using metrics present in the literature. Results suggest that, in such a market, HEAVY does seem to specify daily volatility better, but not necessarily produces better predictions for it, what is, normally, the ultimate goal. The dataset used in this work consists of intraday trades of U.S. Dollar and Ibovespa future contracts from BM&FBovespa.

Does mixed frequency vector error correction model add relevant information to exchange misalignment calculus? Evidence for United States

Real exchange rate is an important macroeconomic price in the economy and a ects economic activity, interest rates, domestic prices, trade and investiments ows among other variables. Methodologies have been developed in empirical exchange rate misalignment studies to evaluate whether a real e ective exchange is overvalued or undervalued. There is a vast body of literature on the determinants of long-term real exchange rates and on empirical strategies to implement the equilibrium norms obtained from theoretical models. This study seeks to contribute to this literature by showing that it is possible to calculate the misalignment from a mixed ointegrated vector error correction framework. An empirical exercise using United States' real exchange rate data is performed. The results suggest that the model with mixed frequency data is preferred to the models with same frequency variables

Industry analysis of the high frequency trading industry : an assessment of the industry boundaries, environment and strategic options

O Mercado Acionário Americano evoluiu rapidamente na última década. Este tornou-se uma arquitetura aberta em que participantes com tecnologia inovadora podem competir de forma eficaz. Várias mudanças regulatórias e inovações tecnológicas permitiram mudanças profundas na estrutura do mercado. Essas mudanças, junto com o desenvolvimento tecnológico de redes de alta velocidade, agiu como um catalisador, dando origem a uma nova forma de negociação, denominada Negociação em Alta Frequência (HFT). As empresas de HFT surgiram e se apropriaram em larga escala do negócio de formação de mercado, no fornecimento de liquidez. Embora HFT tem crescido massivamente, ao longo dos últimos quatro anos, HFT perdeu rentabilidade significativamente, uma vez que mais empresas aderiram ao setor reduzindo as margens. Portanto, diante deste contexto, esta tese buscou apresentar uma breve revisão sobre a atividade de HFT, seguida de uma análise dos limites deste setor, bem como, das características do macroambiente do HFT. Para tanto, a tese realizou uma extensa revisão do histórico literário, documentos públicos qualitativos, tais como, jornais, atas de reunião e relatórios oficiais. A tese empregou um ferramental de análise, Barreiras de Entrada e Mobilidade (Porter, 1980); Modelos de Evolução Setorial (McGahan, 2004); Estrutura do Setor de Informação Intensiva (Sampler, 1998), para analisar os limites do setor de HFT. Adicionalmente, empregou as ferramentas de análise, Modelos de Evolução Setorial (McGahan, 2004) e PESTEL (JOHNSON, SCHOLES, and WHITTINGTON, 2011), para analisar o setor e o contexto que envolve o negócio de HFT. A análise concluiu que as empresas que empregam HFT para atuar e competir no mercado acionário, compoem um setor independente.

Theta-associated high-frequency oscillations (110–160 Hz) in the hippocampus and neocortex

TORT, A. B. L. ; SCHEFFER-TEIXEIRA, R ; Souza, B.C. ; DRAGUHN, A. ; BRANKACK, J. . Theta-associated high-frequency oscillations (110-160 Hz) in the hippocampus and neocortex. Progress in Neurobiology , v. 100, p. 1-14, 2013.

Análise da estrutura e transporte do zooplâncton no estuário do Rio Caravelas (Bahia-Brasil) através do uso do zooscan

Spatial-temporal dynamics of zooplankton in the Caravelas river estuary (Bahia, Brazil). The survey was conducted in order to describe the zooplankton community of the estuary Caravelas (Bahia, Brazil), to quantify and relate the patterns of horizontal and vertical transport with the type of tide (neap and spring) and tidal phase (flood and ebb). Zooplankton samples were collected with the aid of a suction pump (300L), filtered in plankton nets (300μm) and fixed in saline formalin 4%. Samples were collected at a fixed point (A1), near the mouth of the estuary, with samples taken at neap tides and spring tides during the dry and rainy seasons. Samples were collected for 13 hours, at intervals of 1 hour in 3 depths: surface, middle and bottom. Simultaneous collection of biological, we measured the current velocity, temperature and salinity of the water through CTD. In the laboratory, samples were selected for analysis in estereomicroscope, with 25 groups identified, with Copepoda getting the highest number of species. The 168 samples obtained from temporal samples were subsampled and processed on equipment ZooScan, with the aid of software ZooProcess at the end were generated 458.997 vingnettes. 8 taxa were identified automatically, with 16 classified as a semi-automatic. The group Copepoda, despite the limited taxonomic refinement ZooScan, obtained 2 genera and 1 species identified automatically. Among the seasons dry and wet groups Brachyura (zoea), Chaetognatha, and the Calanoid copepods (others), Temora spp., Oithona spp. and Euterpina acutifrons were those who had higher frequency of occurrence, appearing in more than 70% of the samples. Copepoda group showed the largest percentage of relative abundance in both seasons. There was no seasonal variation of total zooplankton, with an average density of 7826±4219 org.m-3 in the dry season, and 7959±3675 org.m-3 in the rainy season, neither between the types and phases of the tides, but seasonal differences were significant recorded for the main zooplankton groups. Vertical stratification was seen for the major zooplankton groups (Brachyura, Chaetognatha, Calanoida (other), Oithona spp, Temora spp. e Euterpina acutifrons). The scale of this stratification varied with the type (square or tide) and tidal phase (flood or ebb). The instantaneous transport was more influenced by current velocity, with higher values observed in spring tides to the total zooplankton, however, there was a variation of this pattern depending on the zooplankton group. According to the data import and export of total zooplankton, the outflow of organisms of the estuary was higher than the input. The results suggest that the estuary of Caravelas may influence the dynamics of organic matter to the adjacent coast, with possible consequences in National Marine Park of Abrolhos

Feeding level and frequency for freshwater angelfish

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The autonomic control and functional significance of the changes in heart rate associated with air breathing in the jeju, Hoplerythrinus unitaeniatus

The jeju is a teleost fish with bimodal respiration that utilizes a modified swim bladder as an air-breathing organ (ABO). Like all air-breathing fish studied to date, jeju exhibit pronounced changes in heart rate (f(H)) during air-breathing events, and it is believed that these may facilitate oxygen uptake (M-O2) from the ABO. The current study employed power spectral analysis (PSA) of f(H) patterns, coupled with instantaneous respirometry, to investigate the autonomic control of these phenomena and their functional significance for the efficacy of air breathing. The jeju obtained less than 5% of total M-O2 (M-tO2) from air breathing in normoxia at 26 degrees C, and PSA of beat-to-beat variability in fH revealed a pattern similar to that of unimodal water-breathing fish. In deep aquatic hypoxia (water P-O2=1 kPa) the jeju increased the frequency of air breathing (f(AB)) tenfold and maintained M-tO2 unchanged from normoxia. This was associated with a significant increase in heart rate variability (HRV), each air breath (AB) being preceded by a brief bradycardia and then followed by a brief tachycardia. These f(H) changes are qualitatively similar to those associated with breathing in unimodal air-breathing vertebrates. Within 20 heartbeats after the AB, however, a beat-to-beat variability in f(H) typical of water-breathing fish was re-established. Pharmacological blockade revealed that both adrenergic and cholinergic tone increased simultaneously prior to each AB, and then decreased after it. However, modulation of inhibitory cholinergic tone was responsible for the major proportion of HRV, including the precise beat-to-beat modulation of f(H) around each AB. Pharmacological blockade of all variations in f(H) associated with air breathing in deep hypoxia did not, however, have a significant effect upon f(AB) or the regulation of M-tO2. Thus, the functional significance of the profound HRV during air breathing remains a mystery.

The wavelet method as an alternative for reducing ionospheric effects from single-frequency GPS receivers

The ionospheric effect is one of the major errors in GPS data processing over long baselines. As a dispersive medium, it is possible to compute its influence on the GPS signal with the ionosphere-free linear combination of L1 and L2 observables, requiring dual-frequency receivers. In the case of single-frequency receivers, ionospheric effects are either neglected or reduced by using a model. In this paper, an alternative for single-frequency users is proposed. It involves multiresolution analysis (MRA) using a wavelet analysis of the double-difference observations to remove the short- and medium-scale ionosphere variations and disturbances, as well as some minor tropospheric effects. Experiments were carried out over three baseline lengths from 50 to 450 km, and the results provided by the proposed method were better than those from dual-frequency receivers. The horizontal root mean square was of about 0.28 m (1 sigma).

Wavelet shrinkage: High frequency multipath reduction from GPS relative positioning

The wavelet transform is used to reduce the high frequency multipath of pseudorange and carrier phase GPS double differences (DDs). This transform decomposes the DD signal, thus separating the high frequencies due to multipath effects. After the decomposition, the wavelet shrinkage is performed by thresholding to eliminate the high frequency component. Then the signal can be reconstructed without the high frequency component. We show how to choose the best threshold. Although the high frequency multipath is not the main multipath error component, its correction provides improvements of about 30% in pseudorange average residuals and 24% in carrier phases. The results also show that the ambiguity solutions become more reliable after correcting the high frequency multipath.