885 resultados para Seleção de portfolio


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Since the seminal works of Markowitz (1952), Sharpe (1964), and Lintner (1965), numerous studies on portfolio selection and performance measure have been based upon the mean-variance framework. However, several researchers (e.g., Arditti (1967, and 1971), Samuelson (1970), and Rubinstein (1973)) argue that the higher moments cannot be neglected unless there is reason to believe that: (i) the asset returns are normally distributed and the investor's utility function is quadratic, or (ii) the empirical evidence demonstrates that higher moments are irrelevant to the investor's decision. Based on the same argument, this dissertation investigates the impact of higher moments of return distributions on three issues concerning the 14 international stock markets.^ First, the portfolio selection with skewness is determined using: the Polynomial Goal Programming in which investor preferences for skewness can be incorporated. The empirical findings suggest that the return distributions of international stock markets are not normally distributed, and that the incorporation of skewness into an investor's portfolio decision causes a major change in the construction of his optimal portfolio. The evidence also indicates that an investor will trade expected return of the portfolio for skewness. Moreover, when short sales are allowed, investors are better off as they attain higher expected return and skewness simultaneously.^ Second, the performance of international stock markets are evaluated using two types of performance measures: (i) the two-moment performance measures of Sharpe (1966), and Treynor (1965), and (ii) the higher-moment performance measures of Prakash and Bear (1986), and Stephens and Proffitt (1991). The empirical evidence indicates that higher moments of return distributions are significant and relevant to the investor's decision. Thus, the higher moment performance measures should be more appropriate to evaluate the performances of international stock markets. The evidence also indicates that various measures provide a vastly different performance ranking of the markets, albeit in the same direction.^ Finally, the inter-temporal stability of the international stock markets is investigated using the Parhizgari and Prakash (1989) algorithm for the Sen and Puri (1968) test which accounts for non-normality of return distributions. The empirical finding indicates that there is strong evidence to support the stability in international stock market movements. However, when the Anderson test which assumes normality of return distributions is employed, the stability in the correlation structure is rejected. This suggests that the non-normality of the return distribution is an important factor that cannot be ignored in the investigation of inter-temporal stability of international stock markets. ^

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This dissertation examines one category of international capital flows, private portfolio investments (private refers to the source of capital). There is an overall lack of a coherent and consistent definition of foreign portfolio investment. We clarify these definitional issues.^ Two main questions that pertain to private foreign portfolio investments (FPI) are explored. The first problem is the phenomenon of home preference, often referred to as home bias. Related to this are the observed cross-investment flows between countries that seem to contradict the textbook rendition of private FPI. A description of the theories purporting to resolve the home preference puzzle (and the cross-investment one) are summarized and evaluated. Most of this literature considers investors from major developed countries. I consider--as well--whether investors in less developed countries have home preference.^ The dissertation shows that home preference is indeed pervasive and profound across countries, in both developed and emerging markets. For the U.S., I examine home bias in both equity and bond holdings as well. I find that home bias is greater when we look at equity and bond holdings than equity holdings solely.^ In this dissertation a model is developed to explain home bias. This model is original and fills a gap in the literature as there have been no satisfactory models that handle at the same time both home preference and cross-border holdings in the context of information asymmetries. This model reflects what we see in the data and permits us to reach certain results by the use of comparative statics methods. The model suggests, counter-intuitively, that as the rate of return in a country relative to the world rate of return increases, home preference decreases. In the context of our relatively simple model we ascribe this result to the higher variance of the now higher return for home assets. We also find, this time as intended, that as risk aversion increases, investors diversify further so that home preference decreases.^ The second question that the dissertation deals with is the volatility of private foreign portfolio investment. Countries that are recipients of these flows have been wary of such flows because of their perceived volatility. Often the contrast is made with the perceived absence of volatility in foreign direct investment flows. I analyze the validity of these concerns using first net flow data and then gross flow data. The results show that FPI is not, in relative terms, more volatile than other flows in our sample of eight countries (half were developed countries and the rest were emerging markets).^ The implication therefore is that restricting FPI flows may be harmful in the sense that private capital may not be allocated efficiently worldwide to the detriment of capital poor economies. More to the point, any such restrictions would in fact be misguided. ^

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This single-case study provides a description and explanation of selected adult students' perspectives on the impact that the development of an experiential learning portfolio had on their understanding of their professional and personal lives. The conceptual framework that undergirded the study included theoretical and empirical studies on adult learning, experiential learning, and the academic quality of nontraditional degree programs with a portfolio component. The study employed qualitative data collection techniques of individual interviews, document review, field notes, and researcher journal. A purposive sample of 8 adult students who completed portfolios as a component of their undergraduate degrees participated in the study. The 4 male and 4 female students who were interviewed represented 4 ethnic/racial groups and ranged in age from 32 to 55 years. Each student's portfolio was read prior to the interview to frame the semi-structured interview questions in light of written portfolio documents. ^ Students were interviewed twice over a 3-month period. The study lasted 8 months from data collection to final presentation of the findings. The data from interview transcriptions and student portfolios were analyzed, categorized, coded, and sorted into 4 major themes and 2 additional themes and submitted to interpretive analysis. ^ Participants' attitudes, perceptions, and opinions of their learning from the portfolio development experience were presented in the findings, which were illustrated through the use of excerpts from interview responses and individual portfolios. The participants displayed a positive reaction to the learning they acquired from the portfolio development process, regardless of their initial concerns about the challenges of creating a portfolio. Concerns were replaced by a greater recognition and understanding of their previous professional and personal accomplishments and their ability to reach future goals. Other key findings included (a) a better understanding of the role work played in their learning and development, (b) a deeper recognition of the impact of mentors and role models throughout their lives, (c) an increase in writing and organizational competencies, and (d) a sense of self-discovery and personal empowerment. ^

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This qualitative case study was limited to an eighteen-hour workshop on “Constructing a Reflective Teacher Portfolio.” The study was conducted at the Nova Center, a research and development school, in the Broward County Public School System. Six participants took part in the study. The study examined the process used by the participants as they constructed their portfolios, explored the reflective aspect of their construction, and investigated the impact that constructing a portfolio had on them and their work. ^ Data was gathered using interviews, observations, and artifacts. Content analysis and the combined frameworks of Van Manen (1977), Smyth (1989), and Pugach and Johnson (1990) were used to examine the data. The data indicates that the portfolios and workshop were not as effective as anticipated in encouraging the participants to examine their work. The following themes emerged as a result of this study: (a) teachers begin constructing their portfolios by gathering material that represents past successes; (b) examining philosophies of education, writing a personal narrative and sharing with colleagues stimulates reflective practice; (c) teachers have difficulty expressing their personal beliefs about education; (d) creating a reflective portfolio is a constructivist process that encourages divergent products; (e) teachers initially do not recognize a strong connection between constructing a portfolio and improving their work; and (f) constructing a portfolio may be an inside-out approach to educational reform. ^ Recommendations were presented to improve the workshop, specifically focusing on teachers examining their practices and learning from students' work. Additional study is needed to evaluate the influence of these changes in the workshop. ^

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Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. ^ A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: (a) increase the efficiency of the portfolio optimization process, (b) implement large-scale optimizations, and (c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. ^ The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. ^ The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH). ^

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This dissertation focused on an increasingly prevalent phenomenon in today's global business environment—strategic alliance portfolio. Building on resource-based view, resource dependency theory and real options theory, this dissertation adopted a multi-dimensional perspective to examine the performance implications, strategic antecedents of alliance portfolio configuration, and its strategic effects on firms' decision-making on their continuing foreign expansion. The dissertation consisted of three interrelated essays, each of which dealt with a specific research question. In the first essay I applied a two-dimensional construct that embraces both alliance relations' and alliance partners' attributes to illustrate alliance portfolio configuration. Based on this framework, a longitudinal study was conducted attempting to explore the performance properties of alliance portfolio configuration. The results revealed that alliance diversity and partner diversity have different relative contributions to firms' economic performance. The relationship between alliance portfolio configuration and firm performance was shaped by degree of multinationality in a curvilinear pattern. The second essay attempted to identify the firm level driving forces of alliance portfolio configuration and how these forces interacting with firms' internationalization influence firms' strategic choices on alliance portfolio configuration. The empirical results indicated that past alliance experience, slack resource and firms' brand images are three critical determinants shaping alliance portfolios, but those shaping relationships are conditioned by firms' multinationality. The third essay primarily employed real options theory to build a conceptual framework, revealing how country-, alliance portfolio-, firm-, and industry level factors and their interactions influence firms' strategic decision-making on post-entry continuing expansion in foreign markets. The two empirical studies were resided in global hospitality and travel industries and use panel data to test the relevant theoretical models. Overall, the dissertation advanced and enriched the theoretical domain of alliance portfolio. It particularly shed valuable insights on three fundamental questions in the domain of alliance portfolio research, namely "if and how alliance portfolios contribute to firms' economic performance"; "what determines the appearance of alliance portfolios”; and "how alliance portfolios affect firms' strategic decision-making". This dissertation also extended the international business and strategic management research on service multinationals' foreign expansion and performance.

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This work presents an application of a hybrid Fuzzy-ELECTRE-TOPSIS multicriteria approach for a Cloud Computing Service selection problem. The research was exploratory, using a case of study based on the actual requirements of professionals in the field of Cloud Computing. The results were obtained by conducting an experiment aligned with a Case of Study using the distinct profile of three decision makers, for that, we used the Fuzzy-TOPSIS and Fuzzy-ELECTRE-TOPSIS methods to obtain the results and compare them. The solution includes the Fuzzy sets theory, in a way it could support inaccurate or subjective information, thus facilitating the interpretation of the decision maker judgment in the decision-making process. The results show that both methods were able to rank the alternatives from the problem as expected, but the Fuzzy-ELECTRE-TOPSIS method was able to attenuate the compensatory character existing in the Fuzzy-TOPSIS method, resulting in a different alternative ranking. The attenuation of the compensatory character stood out in a positive way at ranking the alternatives, because it prioritized more balanced alternatives than the Fuzzy-TOPSIS method, a factor that has been proven as important at the validation of the Case of Study, since for the composition of a mix of services, balanced alternatives form a more consistent mix when working with restrictions.

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Skeletal muscle consists of muscle fiber types that have different physiological and biochemical characteristics. Basically, the muscle fiber can be classified into type I and type II, presenting, among other features, contraction speed and sensitivity to fatigue different for each type of muscle fiber. These fibers coexist in the skeletal muscles and their relative proportions are modulated according to the muscle functionality and the stimulus that is submitted. To identify the different proportions of fiber types in the muscle composition, many studies use biopsy as standard procedure. As the surface electromyography (EMGs) allows to extract information about the recruitment of different motor units, this study is based on the assumption that it is possible to use the EMG to identify different proportions of fiber types in a muscle. The goal of this study was to identify the characteristics of the EMG signals which are able to distinguish, more precisely, different proportions of fiber types. Also was investigated the combination of characteristics using appropriate mathematical models. To achieve the proposed objective, simulated signals were developed with different proportions of motor units recruited and with different signal-to-noise ratios. Thirteen characteristics in function of time and the frequency were extracted from emulated signals. The results for each extracted feature of the signals were submitted to the clustering algorithm k-means to separate the different proportions of motor units recruited on the emulated signals. Mathematical techniques (confusion matrix and analysis of capability) were implemented to select the characteristics able to identify different proportions of muscle fiber types. As a result, the average frequency and median frequency were selected as able to distinguish, with more precision, the proportions of different muscle fiber types. Posteriorly, the features considered most able were analyzed in an associated way through principal component analysis. Were found two principal components of the signals emulated without noise (CP1 and CP2) and two principal components of the noisy signals (CP1 and CP2 ). The first principal components (CP1 and CP1 ) were identified as being able to distinguish different proportions of muscle fiber types. The selected characteristics (median frequency, mean frequency, CP1 and CP1 ) were used to analyze real EMGs signals, comparing sedentary people with physically active people who practice strength training (weight training). The results obtained with the different groups of volunteers show that the physically active people obtained higher values of mean frequency, median frequency and principal components compared with the sedentary people. Moreover, these values decreased with increasing power level for both groups, however, the decline was more accented for the group of physically active people. Based on these results, it is assumed that the volunteers of the physically active group have higher proportions of type II fibers than sedentary people. Finally, based on these results, we can conclude that the selected characteristics were able to distinguish different proportions of muscle fiber types, both for the emulated signals as to the real signals. These characteristics can be used in several studies, for example, to evaluate the progress of people with myopathy and neuromyopathy due to the physiotherapy, and also to analyze the development of athletes to improve their muscle capacity according to their sport. In both cases, the extraction of these characteristics from the surface electromyography signals provides a feedback to the physiotherapist and the coach physical, who can analyze the increase in the proportion of a given type of fiber, as desired in each case.

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Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: a) increase the efficiency of the portfolio optimization process, b) implement large-scale optimizations, and c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH).

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This article proposes a three-step procedure to estimate portfolio return distributions under the multivariate Gram-Charlier (MGC) distribution. The method combines quasi maximum likelihood (QML) estimation for conditional means and variances and the method of moments (MM) estimation for the rest of the density parameters, including the correlation coefficients. The procedure involves consistent estimates even under density misspecification and solves the so-called ‘curse of dimensionality’ of multivariate modelling. Furthermore, the use of a MGC distribution represents a flexible and general approximation to the true distribution of portfolio returns and accounts for all its empirical regularities. An application of such procedure is performed for a portfolio composed of three European indices as an illustration. The MM estimation of the MGC (MGC-MM) is compared with the traditional maximum likelihood of both the MGC and multivariate Student’s t (benchmark) densities. A simulation on Value-at-Risk (VaR) performance for an equally weighted portfolio at 1% and 5% confidence indicates that the MGC-MM method provides reasonable approximations to the true empirical VaR. Therefore, the procedure seems to be a useful tool for risk managers and practitioners.

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This paper examines the effects of higher-order risk attitudes and statistical moments on the optimal allocation of risky assets within the standard portfolio choice model. We derive the expressions for the optimal proportion of wealth invested in the risky asset to show they are functions of portfolio returns third- and fourth-order moments as well as on the investor’s risk preferences of prudence and temperance. We illustrate the relative importance that the introduction of those higher-order effects have in the decision of expected utility maximizers using data for the US.

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This paper introduces a normative view on corporate reputation strategic management. Reputation performance is conceptualised as the outcome of complex processes and social interactions and the lack of a holistic reputation performance management framework is identified. In an attempt to fill this gap, a portfolio-based approach is put forward. Drawing on the foundations of modern portfolio theory we create a portfolio-based reputation management algorithmic model where reputation components and priorities are weighted by decision makers and shape organisational change in an attempt to formulate a corporate reputation strategy. The rationale of this paper is based on the foundational consideration of organisations as choosing he optimal strategy by seeking to maximise their reputation performance while maintaining organisational stability and minimising organisational risk.

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This paper introduces a normative view on corporate reputation management; an algorithmic model for reputation-driven strategic decision making is proposed and corporate reputation is conceptualized as influenced by a selection among organizational priorities. A portfolio-based approach is put forward; we draw on the foundations of portfolio theory and we create a portfolio-based reputation management model where reputation components and priorities are weighted by decision makers and shape organizational change in an attempt to formulate a corporate reputation strategy. The rationale of this paper is based on the foundational consideration of organizations as choosing the optimal strategy by seeking to maximize performance on corporate reputation capital while maintaining organizational stability and minimizing organizational risk.