110 resultados para trading patterns

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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This paper documents that at the individual stock level insiders sales peak many months before a large drop in the stock price, while insiders purchases peak only the month before a large jump. We provide a theoretical explanation for this phenomenon based on trading constraints and asymmetric information. We test our hypothesis against competing stories such as patterns of insider trading driven by earnings announcement dates, or insiders timing their trades to evade prosecution. Finally we provide new evidence regarding crashes and the degree of information asymmetry.

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We construct generating trees with with one, two, and three labels for some classes of permutations avoiding generalized patterns of length 3 and 4. These trees are built by adding at each level an entry to the right end of the permutation, which allows us to incorporate the adjacency condition about some entries in an occurrence of a generalized pattern. We use these trees to find functional equations for the generating functions enumerating these classes of permutations with respect to different parameters. In several cases we solve them using the kernel method and some ideas of Bousquet-Mélou [2]. We obtain refinements of known enumerative results and find new ones.

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"Es tracta d'un projecte dividit en dues parts independents però complementàries, realitzades per autors diferents. Aquest document conté originàriament altre material i/o programari només consultable a la Biblioteca de Ciència i Tecnologia"

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The contributions of this paper are twofold: On the one hand, the paper analyses the factors determining the growth in car ownership in Spain over the last two decades, and, on the other, the paper provides empirical evidence for a controversial methodological issue. From a methodological point of view, the paper compares the two alternative decision mechanisms used for modelling car ownership: ordered-response versus unordered-response mechanisms. A discrete choice model is estimated at three points in time: 1980, 1990 and 2000. The study concludes that on the basis of forecasting performance, the multinomial logit model and the ordered probit model are almost undistinguishable. As for the empirical results, it can be emphasised that income elasticity is not constant and declines as car ownership increases. Besides, households living in rural areas are less sensitive than those living in urban areas. Car ownership is also sensitive to the quality of public transport for those living in the largest cities. The results also confirmed the existence of a generation effect, which will vanish around the year 2020, a weak life-cycle effect, and a positive effect of employment on the number of cars per household. Finally, the change in the estimated coefficients over time reflects an increase in mobility needs and, consequently, an increase in car ownership.

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Climate change has been taking place at unprecedented rates over the past decades. These fast alterations caused by human activities are leading to a global warming of the planet. Warmer temperatures are going to have important effects on vegetation and especially on tropical forests. Insects as well will be affected by climate change. This study tested the hypothesis that higher temperatures lead to a higher insect pressure on vegetation. Visual estimations of leaf damage were recorded and used to assess the extent of herbivory in nine 0.1ha plots along an altitudinal gradient, and therefore a temperature gradient. These estimations were made at both a community level and a species level, on 2 target species. Leaf toughness tests were performed on samples from the target species from each plot. Results showed a strong evidence of increasing insect damage along increasing temperature, with no significant effect from the leaf toughness.

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Within only two decades olive oil developed from a niche product which could hardly be found in food stores outside the producing regions towards an integrated component in the diets of industrial countries. This paper discusses the impacts of the promotion of the “healthy Mediterranean diet” on land use and agro-ecosystems in the producing countries. It examines the dynamics of olive oil production, trade and consumption in the EU15 in the period 1972 to 2003 and the links between dietary patterns, trade and land use. It analyses the underlying socio-economic driving forces behind the increasing spatial disconnect between production and consumption of olive oil in the EU15 and in particular in Spain, the world largest producer during the last three decades. In the observed period olive oil consumption increased 16 fold in the non-producing EU15 countries. In the geographically limited producing regions like Spain, the 5 fold increase in export production was associated with the rapid industrialization of olive production, the conversion of vast Mediterranean landscapes to olive monocultures and a range of environmental pressures. High amounts of subsidies of the European Common Agricultural Policy and feedback loops within production and consumption systems were driving the transformation of the olive oil system. Our analysis indicates the process of change was not immediately driven by increases in demand for olive oil in non-producing countries, but rather by the institutional setting of the European Union and by concerted political interventions.

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This Master Dissertation comprises two parts: a personal reflection and an empirical study. The personal reflection reviews the process of professionalization undergone by its author throughout the Master. The empirical study tackles teacher strategies to elicit knowledge from students in the CLIL classroom and more specifically the purpose of questions in controlled patterns of teacher-student interaction. The theories of relevant authors such as Vigotsky, Mercer and Tsui are used as a framework to analyze the data presented. The analysis shows the different strategies to elicit knowledge used by the teacher and the appropriateness of her questions in the analyzed interaction

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The goal of the study is to determine whether the deficit is syntactic in nature and that aphasic individuals preserve their phonological abilities intact. This has important implications, since it contributes to achieve a more complete characterization of agrammatic comprehension and to report new data from the Romance languages. Here, an experimental task is designed and carried out with six catalan Broca's aphasics, in order to find out whether they preserve their phonological skills. The results establish that Catalan aphasics' comprehension does not result from a phonological impairment

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Abstract: We analyze the realized stock-bond correlation. Gradual transitions between negative and positive stock-bond correlation is accommodated by the smooth transition regression (STR) model. The changes in regime are de…ned by economic and …financial transition variables. Both in sample and out-of- sample results document that STR models with multiple transition variables outperform STR models with a single transition variable. The most important transition variables are the short rate, the yield spread, and the VIX volatility index. Keywords: realized correlation; smooth transition regressions; stock-bond correlation; VIX index JEL Classifi…cations: C22; G11; G12; G17

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The bathyal faunal communities of the NW Mediterranean slopes have been studied consistently in the last two decades, with a special focus on population structure, trophic dynamics and benthopelagic coupling of commercial deep-sea decapod crustaceans and fishes (reviewed in Sardà et al. 2004) and associated species (Cartes and Sardà, 1993; Company and Sardà, 1997, 2000; Cartes et al., 2001; Company et al., 2001, 2003, 2004). One of the major topographic features in the North-western Mediterranean slope is the presence of submarine canyons. Canyons play a major role in funnelling energy and organic matter from the shelf to bathyal and abyssal depths (Puig et al., 2000), but the implications of this enhanced organic supply in the deep-sea benthic communities is still mostly unknown. Trophic supply can follow two major pathways – vertical deposition in the water column (Billett et al., 1983; Baldwin et al., 1998; Lampitt et al., 2001) or down-slope advection on the margins (Puig et al., 2001; Bethoux et al., 2002; Canals et al., 2006) – and can be a limiting factor in the deep-sea, being especially important in the oligotrophic Mediterranean Sea (Sardà et al., 2004). Differences in the quantity, quality and timing of organic matter input to the deep seafloor have been used to explain patterns of biomass and abundance in benthic communities (Levin et al., 1994; Gooday & Turley, 1990; Billett et al., 2001; Galéron et al., 2001; Puig et al., 2001; Gage, 2003) as well as other biological process and in particular the existence of seasonal reproduction (Tyler et al., 1994; Company et al., 2004 (MEPS). Reproduction is a highly energetic process tightly linked to food availability and quality.

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Coded structured light is an optical technique based on active stereovision that obtains the shape of objects. One shot techniques are based on projecting a unique light pattern with an LCD projector so that grabbing an image with a camera, a large number of correspondences can be obtained. Then, a 3D reconstruction of the illuminated object can be recovered by means of triangulation. The most used strategy to encode one-shot patterns is based on De Bruijn sequences. In This work a new way to design patterns using this type of sequences is presented. The new coding strategy minimises the number of required colours and maximises both the resolution and the accuracy

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Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

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In 2000 the European Statistical Office published the guidelines for developing theHarmonized European Time Use Surveys system. Under such a unified framework,the first Time Use Survey of national scope was conducted in Spain during 2002–03. The aim of these surveys is to understand human behavior and the lifestyle ofpeople. Time allocation data are of compositional nature in origin, that is, they aresubject to non-negativity and constant-sum constraints. Thus, standard multivariatetechniques cannot be directly applied to analyze them. The goal of this work is toidentify homogeneous Spanish Autonomous Communities with regard to the typicalactivity pattern of their respective populations. To this end, fuzzy clustering approachis followed. Rather than the hard partitioning of classical clustering, where objects areallocated to only a single group, fuzzy method identify overlapping groups of objectsby allowing them to belong to more than one group. Concretely, the probabilistic fuzzyc-means algorithm is conveniently adapted to deal with the Spanish Time Use Surveymicrodata. As a result, a map distinguishing Autonomous Communities with similaractivity pattern is drawn.Key words: Time use data, Fuzzy clustering; FCM; simplex space; Aitchison distance

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This paper presents a pattern recognition method focused on paintings images. The purpose is construct a system able to recognize authors or art styles based on common elements of his work (here called patterns). The method is based on comparing images that contain the same or similar patterns. It uses different computer vision techniques, like SIFT and SURF, to describe the patterns in descriptors, K-Means to classify and simplify these descriptors, and RANSAC to determine and detect good results. The method are good to find patterns of known images but not so good if they are not.