Detecting Heterogeneous Risk Attitudes with Mixed Gambles

We propose a task for eliciting attitudes toward risk that is close to real-world risky decisions which typically involve gains and losses. The task consists of accepting or rejecting gambles that provide a gain with probability p and a loss with probability 1−p . We employ finite mixture models to uncover heterogeneity in risk preferences and find that (i) behavior is heterogeneous, with one half of the subjects behaving as expected utility maximizers, (ii) for the others, reference-dependent models perform better than those where subjects derive utility from final outcomes, (iii) models with sign-dependent decision weights perform better than those without, and (iv) there is no evidence for loss aversion. The procedure is sufficiently simple so that it can be easily used in field or lab experiments where risk elicitation is not the main experiment.

Idiosyncratic Volatility Puzzle: Influence of Macro-Finance Factors

In this paper, we scrutinize the cross-sectional relation between idiosyncratic volatility and stock returns. As a novelty, the idiosyncratic volatility is obtained by conditioning upon macro-finance factors as well as upon traditional asset pricing factors. The macro-finance factors are constructed from a large pool of macroeconomic and financial variables. Cleaning for macro-finance e§ects reverses the puzzling negative relation between returns and idiosyncratic volatility documented previously. Portfolio analysis shows that the effects from macro-finance factors are economically strong. The relation between idiosyncratic volatility and returns does not vary with the NBER business cycles. The empirical results are highly robust. Keywords: Idiosyncratic volatility puzzle; Macro-finance predictors; Factor analysis; Business cycle. JEL Classifications: G12; G14

Asymptotic analysis of stock price densities and implied volatilities in mixed stochastic models

In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin con- volution of functions de ned on (0;1), and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in mixed stochastic models. Special examples of mixed models are jump-di usion models and stochastic volatility models with jumps. We apply our general results to the Heston model with double exponential jumps, and make a detailed analysis of the asymptotic behavior of the stock price density, the call option pricing function, and the implied volatility in this model. We also obtain similar results for the Heston model with jumps distributed according to the NIG law.

An Engineering Solution for using Coarse Meshes in the Simulation of Delamination with Cohesive Zone Models

This paper presents a methodology to determine the parameters used in the simulation of delamination in composite materials using decohesion finite elements. A closed-form expression is developed to define the stiffness of the cohesive layer. A novel procedure that allows the use of coarser meshes of decohesion elements in large-scale computations is proposed. The procedure ensures that the energy dissipated by the fracture process is correctly computed. It is shown that coarse-meshed models defined using the approach proposed here yield the same results as the models with finer meshes normally used in the simulation of fracture processes

Description of epidemics of coffee rust with neural networks

The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.

Epidemiological analysis of clones and cultivars of potato in soil naturally infested with Ralstonia solanacearum biovar 2

The objectives of this study were to evaluate the progress of Ralstonia solanacearum bacterial potato wilt biovar 2 (race 3) in 14 potato (Solanum tuberosum L.) cultivars or clones, the resistance of potato clone MB 03 (selected in Brasília, Brazil) to race 1 of R. solanacearum, and the occurrence of the pathogen in tubers harvested from asymptomatic potato plants. During the spring (September to the end of November in the southern hemisphere) of 1999 and 2000, 14 cultivars or clones were grown in a field naturally infested with R. solanacearum biovar 2, in Caxias do Sul, RS. The number of wilted potato plants was recorded each week and a disease progress curve plotted, the resistance of the potato genotypes to bacterial wilt being evaluated by determining the area under the curve. Various models were evaluated to fit the curves, with the logistic model being the best fit. At the end of each growing season tubers produced by asymptomatic plants were harvested and stored until budding and then tested for the presence of R. solanacearum. Cultivar Cruza 148 and clone MB 03 were the most resistant but both showed tubers with latent infections. The epidemiological implications of the incidence of R. solanacearum biovar 2 (race 3) in potato crops, as well as the resistance of certain genotypes that may harbor latent infections, are important aspects to be considered in the integrated management of bacterial wilt.

Logistic regression to estimate the welfare of broiler breeders in relation to environmental and behavioral variables

The increasing demand of consumer markets for the welfare of birds in poultry house has motivated many scientific researches to monitor and classify the welfare according to the production environment. Given the complexity between the birds and the environment of the aviary, the correct interpretation of the conduct becomes an important way to estimate the welfare of these birds. This study obtained multiple logistic regression models with capacity of estimating the welfare of broiler breeders in relation to the environment of the aviaries and behaviors expressed by the birds. In the experiment, were observed several behaviors expressed by breeders housed in a climatic chamber under controlled temperatures and three different ammonia concentrations from the air monitored daily. From the analysis of the data it was obtained two logistic regression models, of which the first model uses a value of ammonia concentration measured by unit and the second model uses a binary value to classify the ammonia concentration that is assigned by a person through his olfactory perception. The analysis showed that both models classified the broiler breeder's welfare successfully.

Evaluation of roof slope and exposure with different roofing materials in reduced models of animal production facilities in spring and summer

The present study was conducted at the Department of Rural Engineering and the Department of Animal Morphology and Physiology of FCAV/Unesp, Jaboticabal, SP, Brazil. The objective was to verify the influence of roof slope, exposure and roofing material on the internal temperature of reduced models of animal production facilities. For the development of the research, 48 reduced and dissemble models with dimensions 1.00 × 1.00 × 0.50 m were used. The roof was shed-type, and the models faced to the North or South directions, with 24 models for each side of exposure. Ceramic, galvanized-steel and fibro tiles were used to build the roofs. Slopes varied between 20, 30, 40 and 50% for the ceramic tile and 10, 30, 40 and 50% for the other two. Inside the models, temperature readings were performed at every hour, for 12 months. The results were evaluated in a general linear model in a nested 3 × 4 × 2 factorial arrangement, in which the effects of roofing material and exposure were nested on the factor Slope. Means were compared by the Tukey test at 5% of probability. After analyzing the data, we observed that with the increase in the slope and exposure to the South, there was a drop in the internal temperature within the model at the geographic coordinates of Jaboticabal city (SP/Brazil).

Modelling flexible asset management in industrial maintenance companies and networks

The tightening competition and increasing dynamism have created an emerging need for flexible asset management. This means that the changes of market demand should be responded to with adjustments in the amount of assets tied to the balance sheets of companies. On the other hand, industrial maintenance has recently experienced drastic changes, which have led to an increase in the number of maintenance networks (consisting of customer companies that buy maintenance services, as well as various supplier companies) and inter-organizational partnerships. However, the research on maintenance networks has not followed the changes in the industry. Instead, there is a growing need for new ways of collaboration between partnering companies to enhance the competitiveness of the whole maintenance network. In addition, it is more and more common for companies to pursue lean operations in their businesses. This thesis shows how flexible asset management can increase the profitability of maintenance companies and networks under dynamic operating conditions, and how the additional value can then be shared between the network partners. Firstly, I have conducted a systematic literature review to identify what kind of requirements for asset management models are set by the increasing dynamism. Then I have responded to these requirements by constructing an analytical model for flexible asset management, linking asset management to the profitability and financial state of a company. The thesis uses the model to show how flexible asset management can increase profitability in maintenance companies and networks, and how the created value can be shared in the networks to reach a win-win situation. The research indicates that the existing models for asset management are heterogeneous by nature due to the various definitions of ‘asset management’. I conclude that there is a need for practical asset management models which address assets comprehensively with an inter-organizational, strategic view. The comprehensive perspective, taking all kinds of asset types into account, is needed to integrate the research on asset management with the strategic management of companies and networks. I will show that maintenance companies can improve their profitability by increasing the flexibility of their assets. In maintenance networks, reorganizing the ownership of the assets among the different network partners can create additional value. Finally, I will introduce flexible asset management contracts for maintenance networks. These contracts address the value sharing related to reorganizing the ownership of assets according to the principles of win-win situations.

From protein structure to function with bioinformatics

It has long been known that amino acids are the building blocks for proteins and govern their folding into specific three-dimensional structures. However, the details of this process are still unknown and represent one of the main problems in structural bioinformatics, which is a highly active research area with the focus on the prediction of three-dimensional structure and its relationship to protein function. The protein structure prediction procedure encompasses several different steps from searches and analyses of sequences and structures, through sequence alignment to the creation of the structural model. Careful evaluation and analysis ultimately results in a hypothetical structure, which can be used to study biological phenomena in, for example, research at the molecular level, biotechnology and especially in drug discovery and development. In this thesis, the structures of five proteins were modeled with templatebased methods, which use proteins with known structures (templates) to model related or structurally similar proteins. The resulting models were an important asset for the interpretation and explanation of biological phenomena, such as amino acids and interaction networks that are essential for the function and/or ligand specificity of the studied proteins. The five proteins represent different case studies with their own challenges like varying template availability, which resulted in a different structure prediction process. This thesis presents the techniques and considerations, which should be taken into account in the modeling procedure to overcome limitations and produce a hypothetical and reliable three-dimensional structure. As each project shows, the reliability is highly dependent on the extensive incorporation of experimental data or known literature and, although experimental verification of in silico results is always desirable to increase the reliability, the presented projects show that also the experimental studies can greatly benefit from structural models. With the help of in silico studies, the experiments can be targeted and precisely designed, thereby saving both money and time. As the programs used in structural bioinformatics are constantly improved and the range of templates increases through structural genomics efforts, the mutual benefits between in silico and experimental studies become even more prominent. Hence, reliable models for protein three-dimensional structures achieved through careful planning and thoughtful executions are, and will continue to be, valuable and indispensable sources for structural information to be combined with functional data.

The general equilibrium theory as economic metatheory

Many economists show certain nonconformity relative to the excessive mathematical formalization of economics. This stems from dissatisfaction with the old debate about the lack of correspondence between mainstream theoretical models and reality. Although we do not propose to settle this debate here, this article seeks to associate the mismatch of mathematized models with the reality of the adoption of the hypothetical-deductive method as reproduced by general equilibrium. We begin by defining the main benefits of the mathematization of economics. Secondly, we address traditional criticism leveled against it. We then focus on more recent criticism from Gillies (2005) and Bresser-Pereira (2008). Finally, we attempt to associate the reproduction of the hypothetical-deductive method with a metatheoretical process triggered by Debreu's general equilibrium theory. In this respect, we appropriate the ideas of Weintraub (2002), Punzo (1991), and mainly Woo (1986) to support our hypothesis.

Vitamin D status and latent tuberculosis infection : a preliminary study in a group of healthy Mexican agricultural workers

Vitamin D metabolites are important in the regulation of bone and calcium homeostasis, but also have a more ubiquitous role in the regulation of cell differentiation and immune function. Severely low circulating 25-dihydroxyvitamin D [25(OH)D] concentrations have been associated with the onset of active tuberculosis (TB) in immigrant populations, although the association with latent TB infection (LTBI) has not received much attention. A previous study identified the prevalence of LTBI among a sample of Mexican migrant workers enrolled in Canada's Seasonal Agricultural Workers Program (SA WP) in the Niagara Region of Ontario. The aim of the present study was to determine the vitamin D status of the same sample, and identify if a relationship existed with LTBI. Studies of vitamin D deficiency and active TB are most commonly carried out among immigrant populations to non-endemic regions, in which reactivation of LTBI has occurred. Currently, there is limited knowledge of the association between vitamin D deficiency and LTBI. Entry into Canada ensured that these individuals did not have active TB, and L TBI status was established previously by an interferon-gamma release assay (IGRA) (QuantiFERON-TB Gold In-Tube®, Cellestis Ltd., Australia). Awareness of vitamin D status may enable individuals at risk of deficiency to improve their nutritional health, and those with LTBI to be aware of this risk factor for disease. Prevalence of vitamin D insufficiency among the Mexican migrant workers was determined from serum samples collected in the summer of 2007 as part of the cross sectional LTBI study. Samples were measured for concentrations of the main circulating vitamin D metabolite, 25(OH)D, with a widely used 1251 250HD RIA (DiaSorin Inc.®, Stillwater, MN), and were categorized as deficient «37.5 nmoI/L), insufficient (>37.5 nmollL, < 80 nmol/L) or sufficient (2::80 nmoI/L). Fisher's exact tests and t tests were used to determine if vitamin D status (sufficiency or insufficiency) or 25(OH)D concentrations significantly differed by sex or age categories. Predictors of vitamin D insufficiency and 25(OH)D concentrations were taken from questionnaires carried out during the previous study, and analyzed in the present study using multiple regression prediction models. Fisher's exact test and t test was used to determine if vitamin D status or 25(OH)D concentration differed by LTBI status. Strength of the relationship between interferongamma (IFN-y) concentration (released by peripheral T cells in response to TB antigens) and 25(OH)D concentration was analyzed using a Spearman correlation. Out of 87 participants included in the study (78% male; mean age 38 years), 14 were identified as LTBI positive but none had any signs or symptoms of TB reactivation. Only 30% of the participants were vitamin D sufficient, whereas 68% were insufficient and 2% were deficient. Significant independent predictors of lower 25(OH)D concentrations were sex, number of years enrolled in the SA WP and length of stay in Canada. No significant differences were found between 25(OH)D concentrations and LTBI status. There was a significant moderate correlation between IFN-y and 25(OH)D concentrations ofLTBI-positive individuals. The majority of participants presented with Vitamin D insufficiency but none were severely deficient, indicating that 25(OH)D concentrations do not decrease dramatically in populations who temporarily reside in Canada but go back to their countries of origin during the Canadian winter. This study did not find a statistical relationship between low levels of vitamin D and LTBI which suggests that in the presence of overall good health, lower than ideal levels of 2S(OH)D, may still be exerting a protective immunological effect against LTBI reactivation. The challenge remains to determine a critical 2S(OH)D concentration at which reactivation is more likely to occur.

The Shape of the Risk Premium: Evidence from a Semiparametric Garch Model.

We examine the relationship between the risk premium on the S&P 500 index return and its conditional variance. We use the SMEGARCH - Semiparametric-Mean EGARCH - model in which the conditional variance process is EGARCH while the conditional mean is an arbitrary function of the conditional variance. For monthly S&P 500 excess returns, the relationship between the two moments that we uncover is nonlinear and nonmonotonic. Moreover, we find considerable persistence in the conditional variance as well as a leverage effect, as documented by others. Moreover, the shape of these relationships seems to be relatively stable over time.

Jumps in the Volatility of Financial Markets.

Recent work suggests that the conditional variance of financial returns may exhibit sudden jumps. This paper extends a non-parametric procedure to detect discontinuities in otherwise continuous functions of a random variable developed by Delgado and Hidalgo (1996) to higher conditional moments, in particular the conditional variance. Simulation results show that the procedure provides reasonable estimates of the number and location of jumps. This procedure detects several jumps in the conditional variance of daily returns on the S&P 500 index.

Arbitrage-Based Pricing when Volatility is Stochastic.

The paper investigates the pricing of derivative securities with calendar-time maturities.