915 resultados para market opportunities analysis
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The unemployment of Muslims in Australia was 28 and 25 per cent compared to the national total of around nine per cent in 1986 and 1996 respectively (Australian Bureau of Statistics). This article conceptually analyses the disadvantaged position of the Muslims in the Australian labour market from 1980 to 2001 within a framework of 'structural racism'. It studies the Muslims from three perspectives: first, a comparative study of the qualifications and unemployment of the Muslim labour force in relation to the dominant population. Secondly, it examines the extent of this disadvantaged position in comparison with other ethnic minorities within an historical context. Finally, the basis of structural racism is explored to demonstrate how the Muslims have become systematically victimized. The analysis concludes that Muslims are significantly disadvantaged in Australia on the basis of their ethnicity and religion.
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Women are increasingly active in the participation and consumption of tourism, representing a strong and unique market segment. Knowledge of the needs and preferences of female tourists represents a key success factor in the tourism industry. This preliminary study seeks to capture the underlying reasons for the travel decisions of the residents of the Urban Quadrilátero of Minho, investigating their tourist motivations from a gendered perspective. Insight on tourism motivation may be an important policy tool for tourism planners and managers in the development of products and marketing strategies. The empirical analysis is undertaken based on questionnaires administered in 2012 to residents of the Urban Quadrilátero of Minho. Preliminary results do not reveal significant gender differences in the importance that the local residents place on various tourism motivation factors.
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Tourism represents a major economic activity in Portugal, with an enormous wealth and employment growth potential. A significant proportion of jobs in the industry tourism are occupied by women, given that this industry is characterized by a relatively higher percentage of female employees. Despite the evidence of female progress with regard to their role in the Portuguese labor market, women continue to earn less than their male counterparts. This is clearly the case of the tourism industry, where statistics reveal a persistent gender wage gap. The objective of this paper is to provide empirical evidence on the determinants of gender wage inequality in the tourism industry in northern Portugal. Relying on firm-level wage equations and production functions, gender wage and productivity differentials are estimated and then compared. The comparison of these differentials allows inferring whether observed wage disparities are attributable to relatively lower female productivity, or instead disparities are due to gender wage discrimination. This approach is applied to tourism industry data gathered in the matched employer-employee data set Quadros de Pessoal (Employee Records). The main findings indicate that female employees in the tourism industry in northern Portugal are less productive than their male colleagues and that gender differences in wages are fully explained by gender differences in productivity.
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This paper investigates the performance, investment styles andmanagerial abilities of French socially responsible investment (SRI) funds investing in Europe during crisis and non-crisis periods. Our results show that SRI funds significantly underperformcharacteristics-matched conventional funds during non-crisis periods, but match the performance of their peers duringmarket downturns. The underperformance of SRI funds during good economic states is driven by funds that use negative screens, since funds that use only positive screens performsimilarly to conventional funds across differentmarket conditions. SRI and conventional funds showsignificant differences in risk exposures during non-crisis periods but exhibit much more similar investment styles during crises. Furthermore,we find little evidence of significant differences inmanagerial abilities during bad economic states. Yet, during non-crisis periods, SRI and conventional fund managers exhibit significantly different style-timing abilities and these differences are also related to screening strategies.
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The purpose of this paper is to analyze whether companies with a greater commitment to corporate social responsibility (SRI companies) perform differently on the stock market compared to companies that disregard SRI. Over recent years, this relationship has been taken up at both a theoretical and practical level, and has led to extensive scientific research of an empirical nature involving the examination of the relationships existing between the financial and social, environmental and corporate governance performance of a company and the relationship between SRI and investment decisions in the financial market. More specifically, this work provides empirical evidence for the Spanish market as to whether or not belonging to a group of companies the market classes as sustainable results in return premiums that set them apart from companies classed as conventional, and finds no differences in the stock market performance of companies considered to be SRI or conventional.
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This paper analyzes the risk-return trade-off in European equities considering both temporal and cross-sectional dimensions. In our analysis, we introduce not only the market portfolio but also 15 industry portfolios comprising the entire market. Several bivariate GARCH models are estimated to obtain the covariance matrix between excess market returns and the industrial portfolios and the existence of a risk-return trade-off is analyzed through a cross-sectional approach using the information in all portfolios. It is obtained evidence for a positive and significant risk-return trade-off in the European market. This conclusion is robust for different GARCH specifications and is even more evident after controlling for the main financial crisis during the sample period.
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This paper studies the evolution of the default risk premia for European firms during the years surrounding the recent credit crisis. We employ the information embedded in Credit Default Swaps (CDS) and Moody’s KMV EDF default probabilities to analyze the common factors driving this risk premia. The risk premium is characterized in several directions: Firstly, we perform a panel data analysis to capture the relationship between CDS spreads and actual default probabilities. Secondly, we employ the intensity framework of Jarrow et al. (2005) in order to measure the theoretical effect of risk premium on expected bond returns. Thirdly, we carry out a dynamic panel data to identify the macroeconomic sources of risk premium. Finally, a vector autoregressive model analyzes which proportion of the co-movement is attributable to financial or macro variables. Our estimations report coefficients for risk premium substantially higher than previously referred for US firms and a time varying behavior. A dominant factor explains around 60% of the common movements in risk premia. Additionally, empirical evidence suggests a public-to-private risk transfer between the sovereign CDS spreads and corporate risk premia.
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According to the stock market efficiency theory, it is not possible to consistently beat the market. However, technical analysis is more and more spread as an efficient way to achieve abnormal returns. In fact there is evidence that momentum investing strategies provide abnormal returns in different stock markets, Jegadeesh, N. and Titman, S. (1993), George, T. and Hwang, C. (2004) and Du, D. (2009). In this work we study if like other markets, the Portuguese stock market also allows to obtain abnormal returns, using a strategy that consists in picking stocks according to their past performance. Our work confirms the results of Soares, J. and Serra, A. (2005) and Pereira, P. (2009), showing that an investor can get abnormal returns investing in momentum portfolios. The Portuguese stock market evidences momentum returns in short term, exhibiting reversal in long term.
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In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.
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Dissertação de Mestrado em Finanças Empresariais
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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.
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This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.
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This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimization techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper details some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study based on real data.
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Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.
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Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.