Social construction of economic exchanges: A Weberian approach

The subject-matter of this dissertation is the social construction of economic exchanges, with an emphasis on market transactions. Applying a Weberian approach, the dissertation analyzes the social construction of economic exchanges at the following analytical levels: the agency-level, the institutional-structural level and the comparative-historical level. At the agency-level, the dissertation explores the role that human actors and social actions play in economic exchanges, especially market transactions. Theoretically elaborated and empirically examined is the assumption of market-economic exchanges as particular types of social action. At the institutional-structural level, the dissertation examines the relations of society and culture to market-economic exchanges. The assumption that the market economy is situated in and influenced by a broader social-cultural framework is advanced and evaluated in light of empirical findings. At the comparative-historical level, the dissertation engages in an analysis of the social construction of economic exchanges across various societies and over time. The assumption of the historical specificity of the market economy is reexamined, and the social construction of economic exchanges in traditional, capitalist and post-socialist societies is subject to comparative investigation. In the conclusion, further theoretical, methodological and empirical implications as well as directions for future analyses are discussed. ^

A comprehensive portfolio construction under stochastic environment

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). ^

A study of the top executive conference centers in the United States and an examination of the corresponding corporate meetings market

Introduction: The United States today has become "meeting-conscious." The complexity of conducting business has led to the need for sophisticated coordination of decision-making processes on all levels of the organization. Company meetings have played an increasingly important role in the success and future of many companies. Strategies and decisions are developed at meetings that can determine future policies of crucial importance. Executive training can mean the difference in whether the company will even survive. Large and growing companies have increased their off-premise meeting budgets annually in spite of the state of the economy. however, the rising costs of travel and lodging have made management monitor these budgets more closely than ever. Thus, the need to use every dollar efficiently has compelled companies to examine newer methods of running meetings and alternatives to the usage of typical off-premise meeting facilities. The importance of off-premise meetings in the United States economy has greatly increased due to the billions of dollars spent annually. These factors make it vital to explore the effectiveness of time and monetary expenditures. Up until the mid-1960's, company meetings were held in facilities of various design and purpose, none of which were specifically designed for the small to medium corporate meeting. Upon gathering information concerning the meetings market and the corporate meeting planner, certain individuals endeavored to change the situation. This study is designed to investigate this new concept, which will hereafter be referred to as "conference center." For the purpose of this study, the following two definitions will be used. 1. Conference center - that meeting facility primarily marketing its facilities for the small to medium-sized corporate meeting. The center is operated by specialists aware of market needs in as much detail as are those people working for the company involved. On-premise sleeping rooms are not mandatory provided such facilities are within easy access. 2. Meeting planner - that person within an organization who has primary responsibility for arranging off-premise meetings and all other related items necessary for meeting effectiveness. This person may spend anywhere from 10 to 100l of his time in this capacity. The conference center has effectively satisfied the need for specialized corporate meeting facilities. This study will show the depth of the corporate meetings market and trace the growth and development of this relatively new conference center concept. Information will also be compiled on the top centers in the country. It is hoped that by presenting this research meeting planners will become more aware of the nature and location of these centers, especially for use by the small to medium-sized company. Such exposure of the centers will hopefully increase existing demand and enable the construction of new, innovative centers.

A Comprehensive Portfolio Construction Under Stochastic Environment

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).