Análise experimental do efeito da diversificação em carteiras de ações: a relação entre risco e quantidade de ativos sob a ótica da estratégia ingênua

The objective is to analyze the relationship between risk and number of stocks of a portfolio for an individual investor when stocks are chosen by "naive strategy". For this, we carried out an experiment in which individuals select actions to reproduce this relationship. 126 participants were informed that the risk of first choice would be an asset average of all standard deviations of the portfolios consist of a single asset, and the same procedure should be used for portfolios composed of two, three and so on, up to 30 actions . They selected the assets they want in their portfolios without the support of a financial analysis. For comparison we also tested a hypothetical simulation of 126 investors who selected shares the same universe, through a random number generator. Thus, each real participant is compensated for random hypothetical investor facing the same opportunity. Patterns were observed in the portfolios of individual participants, characterizing the curves for the components of the samples. Because these groupings are somewhat arbitrary, it was used a more objective measure of behavior: a simple linear regression for each participant, in order to predict the variance of the portfolio depending on the number of assets. In addition, we conducted a pooled regression on all observations by analyzing cross-section. The result of pattern occurs on average but not for most individuals, many of which effectively "de-diversify" when adding seemingly random bonds. Furthermore, the results are slightly worse using a random number generator. This finding challenges the belief that only a small number of titles is necessary for diversification and shows that there is only applicable to a large sample. The implications are important since many individual investors holding few stocks in their portfolios

Eficiência e razão de hedge: uma análise dos mercados futuro brasileiros de boi, café, etanol, milho e soja

This research aims to investigate the Hedge Efficiency and Optimal Hedge Ratio for the future market of cattle, coffee, ethanol, corn and soybean. This paper uses the Optimal Hedge Ratio and Hedge Effectiveness through multivariate GARCH models with error correction, attempting to the possible phenomenon of Optimal Hedge Ratio differential during the crop and intercrop period. The Optimal Hedge Ratio must be bigger in the intercrop period due to the uncertainty related to a possible supply shock (LAZZARINI, 2010). Among the future contracts studied in this research, the coffee, ethanol and soybean contracts were not object of this phenomenon investigation, yet. Furthermore, the corn and ethanol contracts were not object of researches which deal with Dynamic Hedging Strategy. This paper distinguishes itself for including the GARCH model with error correction, which it was never considered when the possible Optimal Hedge Ratio differential during the crop and intercrop period were investigated. The commodities quotation were used as future price in the market future of BM&FBOVESPA and as spot market, the CEPEA index, in the period from May 2010 to June 2013 to cattle, coffee, ethanol and corn, and to August 2012 to soybean, with daily frequency. Similar results were achieved for all the commodities. There is a long term relationship among the spot market and future market, bicausality and the spot market and future market of cattle, coffee, ethanol and corn, and unicausality of the future price of soybean on spot price. The Optimal Hedge Ratio was estimated from three different strategies: linear regression by MQO, BEKK-GARCH diagonal model, and BEKK-GARCH diagonal with intercrop dummy. The MQO regression model, pointed out the Hedge inefficiency, taking into consideration that the Optimal Hedge presented was too low. The second model represents the strategy of dynamic hedge, which collected time variations in the Optimal Hedge. The last Hedge strategy did not detect Optimal Hedge Ratio differential between the crop and intercrop period, therefore, unlikely what they expected, the investor do not need increase his/her investment in the future market during the intercrop

A ideologia da encenação: uma análise dos aspectos cênico/ideológicos da encenação produzida pela indústria cultural

The research that led to this dissertation adopted a set of scenic/ideological aspects inherent to the productions of the Culture Industry as its object of research. The intellectual output of Theodor W. Adorno and Max Horkheimer underscored the approaches on this subject, since it provides the same set of scenic/ideological features to be explored because, according to the authors, scenes produced by the culture industry are linked to the dominant ideology, since they act in favor of maintaining the status quo. The first objective was the definition this set of features inherent to the scene produced by the culture industry, through the exploration of literature produced by Adorno and Horkheimer, so it was possible to define a set composed of nine elements: Construction of characters as characteristic types; Stereotypes; Naturalization of Stereotyped language; Simplistic playwriting; Reuse dramatic formula; Love and sexuality as themes of plots; Utilization of tragic element; Objetive representation; Approximation of fiction and reality. The second goal was the analysis of scene produced by the culture industry nowadays, so that it was possible to verify if any scenic/ideological aspects indicated by Adorno and Horkheimer in the mid-twentieth century were present among the productions from this beginning of the twenty-first century. Through the analysis of three soap operas produced in Brazil in 2012, it was found that the nine scenic/ideological aspects as indicated by Adorno and Horkheimer appeared in the observed productions. Additionally, a new scenic/ideological feature, not indicated by Adorno and Horkheimer is present: the merchandising

Análise gráfica de estruturas porosas sobre a ótica da estereologia

In this work we developed a computer simulation program for physics porous structures based on programming language C + + using a Geforce 9600 GT with the PhysX chip, originally developed for video games. With this tool, the ability of physical interaction between simulated objects is enlarged, allowing to simulate a porous structure, for example, reservoir rocks and structures with high density. The initial procedure for developing the simulation is the construction of porous cubic structure consisting of spheres with a single size and with varying sizes. In addition, structures can also be simulated with various volume fractions. The results presented are divided into two parts: first, the ball shall be deemed as solid grains, ie the matrix phase represents the porosity, the second, the spheres are considered as pores. In this case the matrix phase represents the solid phase. The simulations in both cases are the same, but the simulated structures are intrinsically different. To validate the results presented by the program, simulations were performed by varying the amount of grain, the grain size distribution and void fraction in the structure. All results showed statistically reliable and consistent with those presented in the literature. The mean values and distributions of stereological parameters measured, such as intercept linear section of perimeter area, sectional area and mean free path are in agreement with the results obtained in the literature for the structures simulated. The results may help the understanding of real structures.

Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR

This Thesis presents the elaboration of a methodological propose for the development of an intelligent system, able to automatically achieve the effective porosity, in sedimentary layers, from a data bank built with information from the Ground Penetrating Radar GPR. The intelligent system was built to model the relation between the porosity (response variable) and the electromagnetic attribute from the GPR (explicative variables). Using it, the porosity was estimated using the artificial neural network (Multilayer Perceptron MLP) and the multiple linear regression. The data from the response variable and from the explicative variables were achieved in laboratory and in GPR surveys outlined in controlled sites, on site and in laboratory. The proposed intelligent system has the capacity of estimating the porosity from any available data bank, which has the same variables used in this Thesis. The architecture of the neural network used can be modified according to the existing necessity, adapting to the available data bank. The use of the multiple linear regression model allowed the identification and quantification of the influence (level of effect) from each explicative variable in the estimation of the porosity. The proposed methodology can revolutionize the use of the GPR, not only for the imaging of the sedimentary geometry and faces, but mainly for the automatically achievement of the porosity one of the most important parameters for the characterization of reservoir rocks (from petroleum or water)