New findings regarding return autocorrelation anomalies and the importance of non-trading periods

In this paper, differences in return autocorrelation across weekdays havebeen investigated. Our research provides strong evidence of the importanceon non-trading periods, not only weekends and holidays but also overnightclosings, to explain return autocorrelation anomalies. While stock returnsare highly autocorrelated, specially on Mondays, when daily returns arecomputed on a open-to-close basis, they do not exhibit any significantlevel of autocorrelation. Our results are compatible with theinformation processing hypotheses as an explanation of the weekendeffect.

Portable alphas from pension mispricing

We introduce a new dynamic trading strategy based on the systematic misspricing of U.S. companies sponsoring Defined Benefit pension plans. This portfolio produces an average return of 1.51% monthly between 1989 and 2004, with a Sharpe Ratio of 0.26. The returns of the strategy are not explained by those of primary assets. These returns are not related to those of benchmarks in the alternative investments industry either. Hence, we are in the presence of a "pure alpha" strategy that can be ported into a large variety of portfolios to significantly enhance their performance.

A recoverable production planning model

Aware of the importance of developing new alternatives to improve the performance of the companies, our purpose in this paper is to develop a medium term production planning model that deals with the concepts of Partnership and Reverse Logistics. Our model takes advantage of the synergies of integration, developing a model for global production planning that generates the optimal production and purchasing schedule for all the companies integrating a logistic chain. In a second part of the paper we incorporate products returns to the first model proposed, and analyze the implications they have over this model. We use some examples with different configurations of supply chains varying the number of production plants, distribution centers and recovery plants. To solve the model we have combined optimization and simulation procedures.

DNA binding properties of peroxisome proliferator-activated receptor subtypes on various natural peroxisome proliferator response elements. Importance of the 5'-flanking region.

The three subtypes of the peroxisome proliferator-activated receptors (PPARalpha, beta/delta, and gamma) form heterodimers with the 9-cis-retinoic acid receptor (RXR) and bind to a common consensus response element, which consists of a direct repeat of two hexanucleotides spaced by one nucleotide (DR1). As a first step toward understanding the molecular mechanisms determining PPAR subtype specificity, we evaluated by electrophoretic mobility shift assays the binding properties of the three PPAR subtypes, in association with either RXRalpha or RXRgamma, on 16 natural PPAR response elements (PPREs). The main results are as follows. (i) PPARgamma in combination with either RXRalpha or RXRgamma binds more strongly than PPARalpha or PPARbeta to all natural PPREs tested. (ii) The binding of PPAR to strong elements is reinforced if the heterodimerization partner is RXRgamma. In contrast, weak elements favor RXRalpha as heterodimerization partner. (iii) The ordering of the 16 natural PPREs from strong to weak elements does not depend on the core DR1 sequence, which has a relatively uniform degree of conservation, but correlates with the number of identities of the 5'-flanking nucleotides with respect to a consensus element. This 5'-flanking sequence is essential for PPARalpha binding and thus contributes to subtype specificity. As a demonstration of this, the PPARgamma-specific element ARE6 PPRE is able to bind PPARalpha only if its 5'-flanking region is exchanged with that of the more promiscuous HMG PPRE.

Three essays on liquidity risk

Preface In this thesis we study several questions related to transaction data measured at an individual level. The questions are addressed in three essays that will constitute this thesis. In the first essay we use tick-by-tick data to estimate non-parametrically the jump process of 37 big stocks traded on the Paris Stock Exchange, and of the CAC 40 index. We separate the total daily returns in three components (trading continuous, trading jump, and overnight), and we characterize each one of them. We estimate at the individual and index levels the contribution of each return component to the total daily variability. For the index, the contribution of jumps is smaller and it is compensated by the larger contribution of overnight returns. We test formally that individual stocks jump more frequently than the index, and that they do not respond independently to the arrive of news. Finally, we find that daily jumps are larger when their arrival rates are larger. At the contemporaneous level there is a strong negative correlation between the jump frequency and the trading activity measures. The second essay study the general properties of the trade- and volume-duration processes for two stocks traded on the Paris Stock Exchange. These two stocks correspond to a very illiquid stock and to a relatively liquid stock. We estimate a class of autoregressive gamma process with conditional distribution from the family of non-central gamma (up to a scale factor). This process was introduced by Gouriéroux and Jasiak and it is known as Autoregressive gamma process. We also evaluate the ability of the process to fit the data. For this purpose we use the Diebold, Gunther and Tay (1998) test; and the capacity of the model to reproduce the moments of the observed data, and the empirical serial correlation and the partial serial correlation functions. We establish that the model describes correctly the trade duration process of illiquid stocks, but have problems to adjust correctly the trade duration process of liquid stocks which present long-memory characteristics. When the model is adjusted to volume duration, it successfully fit the data. In the third essay we study the economic relevance of optimal liquidation strategies by calibrating a recent and realistic microstructure model with data from the Paris Stock Exchange. We distinguish the case of parameters which are constant through the day from time-varying ones. An optimization problem incorporating this realistic microstructure model is presented and solved. Our model endogenizes the number of trades required before the position is liquidated. A comparative static exercise demonstrates the realism of our model. We find that a sell decision taken in the morning will be liquidated by the early afternoon. If price impacts increase over the day, the liquidation will take place more rapidly.

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This contribution introduces Data Envelopment Analysis (DEA), a performance measurement technique. DEA helps decision makers for the following reasons: (1) By calculating an efficiency score, it indicates if a firm is efficient or has capacity for improvement; (2) By setting target values for input and output, it calculates how much input must be decreased or output increased in order to become efficient; (3) By identifying the nature of returns to scale, it indicates if a firm has to decrease or increase its scale (or size) in order to minimise the average total cost; (4) By identifying a set of benchmarks, it specifies which other firms' processes need to be analysed in order to improve its own practices. This contribution presents the essentials about DEA, alongside a case study to intuitively understand its application. It also introduces Win4DEAP, a software package that conducts efficiency analysis based on DEA methodology. The methodical background of DEA is presented for more demanding readers. Finally, four advanced topics of DEA are treated: adjustment to the environment, preferences, sensitivity analysis and time series data.

Processat de vídeo aplicat a la robòtica

Aquest projecte consisteix en acoblar una càmera web uEye en una de les extremitats d'un robot industrial (ABB Irc5). Aquest robot, es mourà en cas què es detecti una cara a través de la webcam. L'objectiu és intentar que la cara es situï sempre al mig de la imatge captada per la càmera. Podem dividir les tasques d'aquest projecte amb 4 fases diferents. A continuació expliquem les diferents etapes. La Càmera uEye s'encarrega de capturar imatges i passar-les a un PC utilitzant Python. La funció de Detecció de Cares ens indica la posició i dimensions de la cara. Tot seguit, la funció LabJack s'encarrega de canviar els valors digitals de les 5 senyals mitjançant programació amb Python. Per últim el Robot ABB interpreta el valor d'aquestes 5 senyals i es desplaça mitjançant petits increments amb l'objectiu de situar la cara al mig de la imatge capturada.

State-space approach to evaluate the relation between soil physical and chemical properties

The state-space approach is used to evaluate the relation between soil physical and chemical properties in an area cultivated with sugarcane. The experiment was carried out on a Rhodic Kandiudalf in Piracicaba, State of São Paulo, Brazil. Sugarcane was planted on an area of 0.21 ha i.e., in 15 rows 100 m long, spaced 1.4 m. Soil water content, soil organic matter, clay content and aggregate stability were sampled along a transect of 84 points, meter by meter. The state-space approach is used to evaluate how the soil water content is affected by itself and by soil organic matter, clay content, and aggregate stability of neighboring locations, in different combinations, aiming to contribute to a better understanding of the relation among these variables in the soil. Results show that soil water contents were successfully estimated by this approach. Best performances were found when the estimate of soil water content at locations i was related to soil water content, clay content and aggregate stability at locations i-1. Results also indicate that this state-space model using all series describes the soil water content better than any equivalent multiple regression equation.

Essays in general equilibrium asset pricing

ABSTRACT : Research in empirical asset pricing has pointed out several anomalies both in the cross section and time series of asset prices, as well as in investors' portfolio choice. This dissertation aims to discover the forces driving some of these "puzzling" asset pricing dynamics and portfolio decisions observed in the financial market. Through the dissertation I construct and study dynamic general equilibrium models of heterogeneous investors in the presence of frictions and evaluate quantitatively their implications for financial-market asset prices and portfolio choice. I also explore the potential roots of puzzles in international finance. Chapter 1 shows that, by introducing jointly endogenous no-default type of borrowing constraints and heterogeneous beliefs in a dynamic general-equilibrium economy, many empirical features of stock return volatility can be reproduced. While most of the research on stock return volatility is empirical, this paper provides a theoretical framework that is able to reproduce simultaneously the cross section and time series stylized facts concerning stock returns and their volatility. In contrast to the existing theoretical literature related to stock return volatility, I don't impose persistence or regimes in any of the exogenous state variables or in preferences. Volatility clustering, asymmetry in the stock return-volatility relationship, and pricing of multi-factor volatility components in the cross section all arise endogenously as a consequence of the feedback between the binding of no-default constraints and heterogeneous beliefs. Chapters 2 and 3 explore the implications of differences of opinion across investors in different countries for international asset pricing anomalies. Chapter 2 demonstrates that several international finance "puzzles" can be reproduced by a single risk factor which captures heterogeneous beliefs across international investors. These puzzles include: (i) home equity preference; (ii) the dependence of firm returns on local and foreign factors; (iii) the co-movement of returns and international capital flows; and (iv) abnormal returns around foreign firm cross-listing events in the local market. These are reproduced in a setup with symmetric information and in a perfectly integrated world with multiple countries and independent processes producing the same good. Chapter 3 shows that by extending this framework to multiple goods and correlated production processes; the "forward premium puzzle" arises naturally as a compensation for the heterogeneous expectations about the depreciation of the exchange rate held by international investors. Chapters 2 and 3 propose differences of opinion across international investors as the potential resolution of several international finance `puzzles'. In a globalized world where both capital and information flow freely across countries, this explanation seems more appealing than existing asymmetric information or segmented markets theories aiming to explain international finance puzzles.

Genesis of self-organized zebra textures in burial dolomites: Displacive veins, induced stress, and dolomitization

The dolomite veins making up rhythmites common in burial dolomites are not cement infillings of supposed cavities, as in the prevailing view, but are instead displacive veins, veins that pushed aside the host dolostone as they grew. Evidence that the veins are displacive includes a) small transform-fault-like displacements that could not have taken place if the veins were passive cements, and b) stylolites in host rock that formed as the veins grew in order to compensate for the volume added by the veins. Each zebra vein consists of crystals that grow inward from both sides, and displaces its walls via the local induced stress generated by the crystal growth itself. The petrographic criterion used in recent literature to interpret zebra veins in dolomites as cements - namely, that euhedral crystals can grow only in a prior void - disregards evidence to the contrary. The idea that flat voids did form in dolostones is incompatible with the observed optical continuity between the saddle dolomite euhedra of a vein and the replacive dolomite crystals of the host. The induced stress is also the key to the self-organization of zebra veins: In a set of many incipient, randomly-spaced, parallel veins just starting to grow in a host dolostone, each vein¿s induced stress prevents too-close neighbor veins from nucleating, or redissolves them by pressure-solution. The veins that survive this triage are those just outside their neighbors¿s induced stress haloes, now forming a set of equidistant veins, as observed.

The relationship of capitalization period length with market portfolio composition and betas

Beta coefficients are not stable if we modify the observation periods of the returns. The market portfolio composition also varies, whereas changes in the betas are the same, whether they are calculated as regression coefficients or as a ratio of the risk premiums. The instantaneous beta, obtained when the capitalization frequency approaches infinity, may be a useful tool in portfolio selection.

Optimal fiscal policy in overlapping generations models

[eng] This paper provides, from a theoretical and quantitative point of view, an explanation of why taxes on capital returns are high (around 35%) by analyzing the optimal fiscal policy in an economy with intergenerational redistribution. For this purpose, the government is modeled explicitly and can choose (and commit to) an optimal tax policy in order to maximize society's welfare. In an infinitely lived economy with heterogeneous agents, the long run optimal capital tax is zero. If heterogeneity is due to the existence of overlapping generations, this result in general is no longer true. I provide sufficient conditions for zero capital and labor taxes, and show that a general class of preferences, commonly used on the macro and public finance literature, violate these conditions. For a version of the model, calibrated to the US economy, the main results are: first, if the government is restricted to a set of instruments, the observed fiscal policy cannot be disregarded as sub optimal and capital taxes are positive and quantitatively relevant. Second, if the government can use age specific taxes for each generation, then the age profile capital tax pattern implies subsidizing asset returns of the younger generations and taxing at higher rates the asset returns of the older ones.

Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Inter-relation between soybean yield and soil compaction under degraded pasture in Brazilian Savannah

The Cerrado (Brazilian Savannah) plays an important economic and financial role in the nation, since the pastures of this biome feed cattle for half of the domestic bovine meat productivity, and its agricultural fields produce a third of the country's grain. The variability and spatial dependence between the soil physical attributes and soybean yield were evaluated in a crop rotation planted on a degraded brachiaria pasture, on a dystroferric Red Latosol of an experimental farm of the State University of São Paulo (UNESP), in the 2005/2006 growing season. The linear and spatial correlations between these attributes were also studied, to determine conditions that would allow increased agricultural productivity. In the above pasture area, a grid was installed with 124 plots, spaced 10.0 x 10.0 m and 5.0 x 5.0 m apart, in a total area of 7,500 m². From the linear and spatial point of view, the high grain yield can be explained by the number of grains per plant and soil macroporosity. The high variability observed for most soil properties indicated that the crop - livestock integration system results in environmental heterogeneity of the soil.

MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data.

A recurring task in the analysis of mass genome annotation data from high-throughput technologies is the identification of peaks or clusters in a noisy signal profile. Examples of such applications are the definition of promoters on the basis of transcription start site profiles, the mapping of transcription factor binding sites based on ChIP-chip data and the identification of quantitative trait loci (QTL) from whole genome SNP profiles. Input to such an analysis is a set of genome coordinates associated with counts or intensities. The output consists of a discrete number of peaks with respective volumes, extensions and center positions. We have developed for this purpose a flexible one-dimensional clustering tool, called MADAP, which we make available as a web server and as standalone program. A set of parameters enables the user to customize the procedure to a specific problem. The web server, which returns results in textual and graphical form, is useful for small to medium-scale applications, as well as for evaluation and parameter tuning in view of large-scale applications, requiring a local installation. The program written in C++ can be freely downloaded from ftp://ftp.epd.unil.ch/pub/software/unix/madap. The MADAP web server can be accessed at http://www.isrec.isb-sib.ch/madap/.