895 resultados para Mobilization of financial resources
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We analyse whether the quality of firms’ Financial Reports (FRQ) produces any effect on their performance. Bradshaw et al. (2004) and Gelos and Wei (2005) call attention to the fact that the international capital movements is affected by FRQ. Following Schipper and Vicent (2003) we use the abnormal accruals to access earnings quality. For seventeen European countries, we found evidence that FRQ produces a positive impact on firm’s performance. This finding indicates that mangers are not opportunists and tends to make decisions to defend the firm’s best interests. This result is robust since it does not depend on the accounting firms’ performance proxy (ROA/ROE). In addition, it is also consistent when we use data in time series and in cross-sectional and when we estimate regression with lagged or the current year information about abnormal accruals.
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A multilevel negotiation mechanism for operating smart grids and negotiating in electricity markets considers the advantages of virtual power player management.
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An auction model is used to increase the individual profits for market players with products they do not use. A Financial Transmission Rights Auction has the goal of trade transmission rights between Bidders and helps them raise their own profits. The ISO plays a major rule on keep the system in technical limits without interfere on the auctions offers. In some auction models the ISO decide want bids are implemented on the network, always with the objective maximize the individual profits for all bidders in the auction. This paper proposes a methodology for a Financial Transmission Rights Auction and an informatics application. The application receives offers from the purchase and sale side and considers bilateral contracts as Base Case. This goal is maximize the individual profits within the system in their technical limits. The paper includes a case study for the 30 bus IEEE test case.
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OBJECTIVE: To identify the effects of decentralization on health financing and governance policies in Mexico from the perspective of users and providers. METHODS: A cross-sectional study was carried out in four states that were selected according to geopolitical and administrative criteria. Four indicators were assessed: changes and effects on governance, financing sources and funds, the final destination of resources, and fund allocation mechanisms. Data collection was performed using in-depth interviews with health system key personnel and community leaders, consensus techniques and document analyses. The interviews were transcribed and analyzed by thematic segmentation. RESULTS: The results show different effectiveness levels for the four states regarding changes in financing policies and community participation. Effects on health financing after decentralization were identified in each state, including: greater participation of municipal and state governments in health expenditure, increased financial participation of households, greater community participation in low-income states, duality and confusion in the new mechanisms for coordination among the three government levels, absence of an accountability system, lack of human resources and technical skills to implement, monitor and evaluate changes in financing. CONCLUSIONS: In general, positive and negative effects of decentralization on health financing and governance were identified. The effects mentioned by health service providers and users were related to a diversification of financing sources, a greater margin for decisions around the use and final destination of financial resources and normative development for the use of resources. At the community level, direct financial contributions were mentioned, as well as in-kind contributions, particularly in the form of community work.
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Mestrado em Contabilidade
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Understanding the determinants of international performance, and in particular, export performance is key for the success of international companies. Research in this area focuses mainly on how resources and capabilities allow companies to gain competitive advantage and superior performance in external markets. Building on the Resource-Based View (RBV) and the Dynamic Capabilities Approach (DCA), this study aims at analysing the effect of intangible resources and capabilities on export performance. Specifically, this study focuses on the proposition that entrepreneurial orientation potentiates the attraction of intangible resources, namely relational and informational resources. Moreover, we propose that these resources impact export performance both directly and indirectly through dynamic capabilities.
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Power law PL and fractional calculus are two faces of phenomena with long memory behavior. This paper applies PL description to analyze different periods of the business cycle. With such purpose the evolution of ten important stock market indices DAX, Dow Jones, NASDAQ, Nikkei, NYSE, S&P500, SSEC, HSI, TWII, and BSE over time is studied. An evolutionary algorithm is used for the fitting of the PL parameters. It is observed that the PL curve fitting constitutes a good tool for revealing the signal main characteristics leading to the emergence of the global financial dynamic evolution.
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This paper presents a novel method for the analysis of nonlinear financial and economic systems. The modeling approach integrates the classical concepts of state space representation and time series regression. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the dynamical behavior. The results reveal that business cycles can be clearly revealed, while the noise effects common in financial indices can elegantly be filtered out of the results.
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The goal of this study is to analyze the dynamical properties of financial data series from nineteen worldwide stock market indices (SMI) during the period 1995–2009. SMI reveal a complex behavior that can be explored since it is available a considerable volume of data. In this paper is applied the window Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional order systems.
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The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.
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"The purpose of the XII Iberian-Italian Congress of Financial and Actuarial Mathematics is to provide a meeting point for researchers in Financial Economics from different countries and research backgrounds in universities, government or financial institutions. In fact, the Congress which is currently taking place in Lisbon has been organized to encourage communication and debate among the participants as well as to reinforce the bonds between us.The current edition of the Congress is characterized by the quality and diversity of the papers that have been submitted with special attention to the International Financial Crisis and measures of risk in different financial markets. However, as the Congress Program indicates, there are also parallel sessions about traditional topics in finance such as asset pricing, insurance, corporate finance, etc.Although this Congress has always been organized alternately between Spain and Italy, this year we have the great pleasure of celebrating it in Portugal which will be included as a permanent partner." [prefácio]
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This paper proposes and reports the development of an open source solution for the integrated management of Infrastructure as a Service (IaaS) cloud computing resources, through the use of a common API taxonomy, to incorporate open source and proprietary platforms. This research included two surveys on open source IaaS platforms (OpenNebula, OpenStack and CloudStack) and a proprietary platform (Parallels Automation for Cloud Infrastructure - PACI) as well as on IaaS abstraction solutions (jClouds, Libcloud and Deltacloud), followed by a thorough comparison to determine the best approach. The adopted implementation reuses the Apache Deltacloud open source abstraction framework, which relies on the development of software driver modules to interface with different IaaS platforms, and involved the development of a new Deltacloud driver for PACI. The resulting interoperable solution successfully incorporates OpenNebula, OpenStack (reuses pre-existing drivers) and PACI (includes the developed Deltacloud PACI driver) nodes and provides a Web dashboard and a Representational State Transfer (REST) interface library. The results of the exchanged data payload and time response tests performed are presented and discussed. The conclusions show that open source abstraction tools like Deltacloud allow the modular and integrated management of IaaS platforms (open source and proprietary), introduce relevant time and negligible data overheads and, as a result, can be adopted by Small and Medium-sized Enterprise (SME) cloud providers to circumvent the vendor lock-in problem whenever service response time is not critical.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores
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Context-aware recommendation of personalised tourism resources is possible because of personal mobile devices and powerful data filtering algorithms. The devices contribute with computing capabilities, on board sensors, ubiquitous Internet access and continuous user monitoring, whereas the filtering algorithms provide the ability to match the profile (interests and the context) of the tourist against a large knowledge bases of tourism resources. While, in terms of technology, personal mobile devices can gather user-related information, including the user context and access multiple data sources, the creation and maintenance of an updated knowledge base of tourism-related resources requires a collaborative approach due to the heterogeneity, volume and dynamic nature of the resources. The current PhD thesis aims to contribute to the solution of this problem by adopting a Crowdsourcing approach for the collaborative maintenance of the knowledge base of resources, Trust and Reputation for the validation of uploaded resources as well as publishers, Big Data for user profiling and context-aware filtering algorithms for the personalised recommendation of tourism resources.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics