18 resultados para Capital Asset Pricing Model

em Universidad Politécnica de Madrid


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The study examines the Capital Asset Pricing Model (CAPM) for the mining sector using weekly stock returns from 27 companies traded on the New York Stock Exchange (NYSE) or on the London Stock Exchange (LSE) for the period of December 2008 to December 2010. The results support the use of the CAPM for the allocation of risk to companies. Most companies involved in precious metals (particularly gold), which have a beta value less than unity (Table 1), have been actuated as shelter values during the financial crisis. Values of R2 do not shown very explanatory power of fitted models (R2 < 70 %). Estimated coefficients beta are not sufficient to determine the expected returns on securities but the results of the tests conducted on sample data for the period analysed do not appear to clearly reject the CAPM

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El capital financiero es muy volátil y si el inversor no obtiene una remuneración adecuada al riesgo que asume puede plantearse el retirar su capital del patrimonio de la empresa y, en consecuencia, producir un cambio estructural en cualquier sector de la economía. El objetivo principal es el estudio de los coeficientes de regresión (coeficiente beta) de los modelos de valoración de activos empleados en Economía Financiera, esto es, el estudio de la variación de la rentabilidad de los activos en función de los cambios que suceden en los mercados. La elección de los modelos utilizados se justifica por la amplia utilización teórica y empírica de los mismos a lo largo de la historia de la Economía Financiera. Se han aplicado el modelo de valoración de activos de mercado (capital asset pricing model, CAPM), el modelo basado en la teoría de precios de arbitraje (arbitrage pricing theory, APT) y el modelo de tres factores de Fama y French (FF). Estos modelos se han aplicado a los rendimientos mensuales de 27 empresas del sector minero que cotizan en la bolsa de Nueva York (New York Stock Exchange, NYSE) o en la de Londres (London Stock Exchange, LSE), con datos del período que comprende desde Enero de 2006 a Diciembre de 2010. Los resultados de series de tiempo y sección cruzada tanto para CAPM, como para APT y FF producen varios errores, lo que sugiere que muchas empresas del sector no han podido obtener el coste de capital. También los resultados muestran que las empresas de mayor riesgo tienden a tener una menor rentabilidad. Estas conclusiones hacen poco probable que se mantenga en el largo plazo el equilibrio actual y puede que sea uno de los principales factores que impulsen un cambio estructural en el sector minero en forma de concentraciones de empresas. ABSTRACT Financial capital is highly volatile and if the investor does not get adequate compensation for the risk faced he may consider withdrawing his capital assets from the company and consequently produce a structural change in any sector of the economy. The main purpose is the study of the regression coefficients (beta) of asset pricing models used in financial economics, that is, the study of variation in profitability of assets in terms of the changes that occur in the markets. The choice of models used is justified by the extensive theoretical and empirical use of them throughout the history of financial economics. Have been used the capital asset pricing model, CAPM, the model XII based on the arbitrage pricing theory (APT) and the three-factor model of Fama and French (FF). These models have been applied to the monthly returns of 27 mining companies listed on the NYSE (New York Stock Exchange) or LSE(London Stock Exchange), using data from the period covered from January 2006 to December 2010. The results of time series and cross sectional regressions for CAPM, APT and FF produce some errors, suggesting that many companies have failed to obtain the cost of capital. Also the results show that higher risk firms tend to have lower profitability. These findings make it unlikely to be mainteined over the long term the current status and could drive structural change in the mining sector in the form of mergers.

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The current economic crisis has meant, particularly in Spain, the almost cessation of new buildings construction. This deep crisis will mean in future an irreversible change in the Spanish construction model, based to date almost exclusively on the brick. After focusing on the Spanish property boom and examining its impact on the concept of housing (in a few years the house has moved forward from being contemplated exclusively as a primary good to be also considered a capital asset), we analyse the influence that this transformation has had on architecture (housing typology, building methods, the architectural profession and the architect training) and offers architectural alternatives –trough the university– to the present crisis. The project “Houses built from accommodating cabins” is part of a larger research within the line “Modular Architecture” developed by the Research Group “Design and Industrial Production”, belonging to the Technical University of Madrid, which aims to respond to the need for decent housing at an affordable price, by offering through Internet the plans, resources and other technical details required to build a house oneself. The proposed houses are built from the combination of industrially made modules (accommodation cabins, which are prefabricated modules usually used as provisional constructions in conventional building works), prefabricated subsystems and other catalogue components available on the market, all they set together by dry joints.

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(Matsukawa and Habeck, 2007) analyse the main instruments for risk mitigation in infrastructure financing with Multilateral Financial Institutions (MFIs). Their review coincided with the global financial crisis of 2007-08, and is highly relevant in current times considering the sovereign debt crisis, the lack of available capital and the increases in bank regulation in Western economies. The current macroeconomic environment has seen a slowdown in the level of finance for infrastructure projects, as they pose a higher credit risk given their requirements for long term investments. The rationale for this work is to look for innovative solutions that are focused on the credit risk mitigation of infrastructure and energy projects whilst optimizing the economic capital allocation for commercial banks. This objective is achieved through risk-sharing with MFIs and looking for capital relief in project finance transactions. This research finds out the answer to the main question: "What is the impact of risk-sharing with MFIs on project finance transactions to increase their efficiency and viability?", and is developed from the perspective of a commercial bank assessing the economic capital used and analysing the relevant variables for it: Probability of Default, Loss Given Default and Recovery Rates, (Altman, 2010). An overview of project finance for the infrastructure and energy sectors in terms of the volume of transactions worldwide is outlined, along with a summary of risk-sharing financing with MFIs. A review of the current regulatory framework beneath risk-sharing in structured finance with MFIs is also analysed. From here, the impact of risk-sharing and the diversification effect in infrastructure and energy projects is assessed, from the perspective of economic capital allocation for a commercial bank. CreditMetrics (J. P. Morgan, 1997) is applied over an existing well diversified portfolio of project finance infrastructure and energy investments, working with the main risk capital measures: economic capital, RAROC, and EVA. The conclusions of this research show that economic capital allocation on a portfolio of project finance along with risk-sharing with MFIs have a huge impact on capital relief whilst increasing performance profitability for commercial banks. There is an outstanding diversification effect due to the portfolio, which is combined with risk mitigation and an improvement in recovery rates through Partial Credit Guarantees issued by MFIs. A stress test scenario analysis is applied to the current assumptions and credit risk model, considering a downgrade in the rating for the commercial bank (lender) and an increase of default in emerging countries, presenting a direct impact on economic capital, through an increase in expected loss and a decrease in performance profitability. Getting capital relief through risk-sharing makes it more viable for commercial banks to finance infrastructure and energy projects, with the beneficial effect of a direct impact of these investments on GDP growth and employment. The main contribution of this work is to promote a strategic economic capital allocation in infrastructure and energy financing through innovative risk-sharing with MFIs and economic pricing to create economic value added for banks, and to allow the financing of more infrastructure and energy projects. This work suggests several topics for further research in relation to issues analysed. (Matsukawa and Habeck, 2007) analizan los principales instrumentos de mitigación de riesgos en las Instituciones Financieras Multilaterales (IFMs) para la financiación de infraestructuras. Su presentación coincidió con el inicio de la crisis financiera en Agosto de 2007, y sus consecuencias persisten en la actualidad, destacando la deuda soberana en economías desarrolladas y los problemas capitalización de los bancos. Este entorno macroeconómico ha ralentizado la financiación de proyectos de infraestructuras. El actual trabajo de investigación tiene su motivación en la búsqueda de soluciones para la financiación de proyectos de infraestructuras y de energía, mitigando los riesgos inherentes, con el objeto de reducir el consumo de capital económico en los bancos financiadores. Este objetivo se alcanza compartiendo el riesgo de la financiación con IFMs, a través de estructuras de risk-sharing. La investigación responde la pregunta: "Cuál es el impacto de risk-sharing con IFMs, en la financiación de proyectos para aumentar su eficiencia y viabilidad?". El trabajo se desarrolla desde el enfoque de un banco comercial, estimando el consumo de capital económico en la financiación de proyectos y analizando las principales variables del riesgo de crédito, Probability of Default, Loss Given Default and Recovery Rates, (Altman, 2010). La investigación presenta las cifras globales de Project Finance en los sectores de infraestructuras y de energía, y analiza el marco regulatorio internacional en relación al consumo de capital económico en la financiación de proyectos en los que participan IFMs. A continuación, el trabajo modeliza una cartera real, bien diversificada, de Project Finance de infraestructuras y de energía, aplicando la metodología CreditMet- rics (J. P. Morgan, 1997). Su objeto es estimar el consumo de capital económico y la rentabilidad de la cartera de proyectos a través del RAROC y EVA. La modelización permite estimar el efecto diversificación y la liberación de capital económico consecuencia del risk-sharing. Los resultados muestran el enorme impacto del efecto diversificación de la cartera, así como de las garantías parciales de las IFMs que mitigan riesgos, mejoran el recovery rate de los proyectos y reducen el consumo de capital económico para el banco comercial, mientras aumentan la rentabilidad, RAROC, y crean valor económico, EVA. En escenarios económicos de inestabilidad, empeoramiento del rating de los bancos, aumentos de default en los proyectos y de correlación en las carteras, hay un impacto directo en el capital económico y en la pérdida de rentabilidad. La liberación de capital económico, como se plantea en la presente investigación, permitirá financiar más proyectos de infraestructuras y de energía, lo que repercutirá en un mayor crecimiento económico y creación de empleo. La principal contribución de este trabajo es promover la gestión activa del capital económico en la financiación de infraestructuras y de proyectos energéticos, a través de estructuras innovadoras de risk-sharing con IFMs y de creación de valor económico en los bancos comerciales, lo que mejoraría su eficiencia y capitalización. La aportación metodológica del trabajo se convierte por su originalidad en una contribución, que sugiere y facilita nuevas líneas de investigación académica en las principales variables del riesgo de crédito que afectan al capital económico en la financiación de proyectos.

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Software testing is a key aspect of software reliability and quality assurance in a context where software development constantly has to overcome mammoth challenges in a continuously changing environment. One of the characteristics of software testing is that it has a large intellectual capital component and can thus benefit from the use of the experience gained from past projects. Software testing can, then, potentially benefit from solutions provided by the knowledge management discipline. There are in fact a number of proposals concerning effective knowledge management related to several software engineering processes. Objective: We defend the use of a lesson learned system for software testing. The reason is that such a system is an effective knowledge management resource enabling testers and managers to take advantage of the experience locked away in the brains of the testers. To do this, the experience has to be gathered, disseminated and reused. Method: After analyzing the proposals for managing software testing experience, significant weaknesses have been detected in the current systems of this type. The architectural model proposed here for lesson learned systems is designed to try to avoid these weaknesses. This model (i) defines the structure of the software testing lessons learned; (ii) sets up procedures for lesson learned management; and (iii) supports the design of software tools to manage the lessons learned. Results: A different approach, based on the management of the lessons learned that software testing engineers gather from everyday experience, with two basic goals: usefulness and applicability. Conclusion: The architectural model proposed here lays the groundwork to overcome the obstacles to sharing and reusing experience gained in the software testing and test management. As such, it provides guidance for developing software testing lesson learned systems.

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This article presents an alternative approach to the decision-making process in transport strategy design. The study explores the possibility of integrating forecasting, assessment and optimization procedures in support of a decision-making process designed to reach the best achievable scenario through mobility policies. Long-term evaluation, as required by a dynamic system such as a city, is provided by a strategic Land-Use and Transport Interaction (LUTI) model. The social welfare achieved by implementing mobility LUTI model policies is measured through a cost-benefit analysis and maximized through an optimization process throughout the evaluation period. The method is tested by optimizing a pricing policy scheme in Madrid on a cordon toll in a context requiring system efficiency, social equity and environmental quality. The optimized scheme yields an appreciable increase in social surplus through a relatively low rate compared to other similar pricing toll schemes. The results highlight the different considerations regarding mobility impacts on the case study area, as well as the major contributors to social welfare surplus. This leads the authors to reconsider the cost-analysis approach, as defined in the study, as the best option for formulating sustainability measures.

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Several international studies have analyzed the acceptability of road pricing schemes by means of an attitude survey in combination with the results of a stated choice experiment using both a descriptive analysis and a discrete-choice model with binary choice (?accept? or ?not accept? the toll). However, the use of hybrid discrete choice models constitutes an innovative alternative for integrating subjective attitudes and perceptions deriving from the survey of attitudes with the more objective variables from the stated choice experiment. This paper analyzes the results of applying these models to measure the acceptability of interurban road pricing among different groups of stakeholders (road freight and passenger operators, highway concessionaires, and associations of private car users) with qualitatively significant opinions on road pricing measures. Our results show that hybrid models are better suited to explaining the acceptability of a road pricing scheme by different groups of stakeholders than a separate analysis of the survey of attitudes and a discrete-choice model applied on a stated choice experiment. A particular finding was that the strong psycho-social latent variable of the perception of fairness explains the rejection or acceptance of a toll scheme by road stakeholders.

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A main factor to the success of any organization process improvement effort is the Process Asset Library implementation that provides a central database accessible by anyone at the organization. This repository includes any process support materials to help process deployment. Those materials are composed of organization's standard software process, software process related documentation, descriptions of the software life cycles, guidelines, examples, templates, and any artefacts that the organization considers useful to help the process improvement. This paper describe the structure and contents of the Web-based Process Asset Library for Small businesses and small groups within large organizations. This library is structured using CMMI as reference model in order to implement those Process Areas described by this model.

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Assessing users’ benefit in a transport policy implementation has been studied by many researchers using theoretical or empirical measures. However, few of them measure users’ benefit in a different way from the consumer surplus. Therefore, this paper aims to assess a new measure of user benefits by weighting consumer surplus in order to include equity assessment for different transport policies simulated in a dynamic middle-term LUTI model adapted to the case study of Madrid. Three different transport policies, including road pricing, parking charge and public transport improvement have been simulated through the Metropolitan Activity Relocation Simulator, MARS, the LUTI calibrated model for Madrid). A social welfare function (WF) is defined using a cost benefit analysis function that includes mainly costs and benefits of users and operators of the transport system. Particularly, the part of welfare function concerning the users, (i.e. consumer surplus), is modified by a compensating weight (CW) which represents the inverse of household income level. Based on the modified social welfare function, the effects on the measure of users benefits are estimated and compared with the old WF ́s results as well. The result of the analysis shows that road pricing leads a negative effect on the users benefits specially on the low income users. Actually, the road pricing and parking charge implementation results like a regressive policy especially at long term. Public transport improvement scenario brings more positive effects on low income user benefits. The integrated (road pricing and increasing public services) policy scenario is the one which receive the most user benefits. The results of this research could be a key issue to understanding the relationship between transport systems policies and user benefits distribution in a metropolitan context.

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Assessing social benefits in transport policy implementation has been studied by many researchers using theoretical or empirical measures. However, few of them measure social benefit using different discount rates including the inter-temporal preferences rate of users, the private investment discount rate and the inter-temporal preferences rate of the government. In general, the social discount rate used is the same for all social actors. Therefore, this paper aims to assess a new method by integrating different types of discount rate belonging to different social actors in order to measure the real benefits of each actor in the short, medium and long term. A dynamic simulation is provided by a strategic Land-Use and Transport Interaction (LUTI) model. The method is tested by optimizing a cordon toll scheme in Madrid considering socio- economic efficiency and environmental criteria. Based on the modified social welfare function (WF), the effects on the measure of social benefits are estimated and compared with the classical WF results as well. The results of this research could be a key issue to understanding the relationship between transport system policies and social actors' benefits distribution in a metropolitan context. The results show that the use of more suitable discount rates for each social actor had an effect on the selection and definition of optimal strategy of congestion pricing. The usefulness of the measure of congestion toll declines more quickly overtime.

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Many researchers have used theoretical or empirical measures to assess social benefits in transport policy implementation. However, few have measured social benefits by using discount rates, including the intertemporal preference rate of users, the private investment discount rate, and the intertemporal preference rate of the government. In general, the social discount rate used is the same for all social actors. This paper aims to assess a new method by integrating different types of discount rates belonging to different social actors to measure the real benefits of each actor in the short term, medium term, and long term. A dynamic simulation is provided by a strategic land use and transport interaction model. The method was tested by optimizing a cordon toll scheme in Madrid, Spain. Socioeconomic efficiency and environmental criteria were considered. On the basis of the modified social welfare function, the effects on the measure of social benefits were estimated and compared with the classical welfare function measures. The results show that the use of more suitable discount rates for each social actor had an effect on the selection and definition of optimal strategy of congestion pricing. The usefulness of the measure of congestion toll declines more quickly over time. This result could be the key to understanding the relationship between transport system policies and the distribution of social actors? benefits in a metropolitan context.

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This article presents an alternative approach to the decision-making process in transport strategy design. The study explores the possibility of integrating forecasting, assessment and optimization procedures in support of a decision-making process designed to reach the best achievable scenario through mobility policies. Long-term evaluation, as required by a dynamic system such as a city, is provided by a strategic Land-Use and Transport Interaction (LUTI) model. The social welfare achieved by implementing mobility LUTI model policies is measured through a cost-benefit analysis and maximized through an optimization process throughout the evaluation period. The method is tested by optimizing a pricing policy scheme in Madrid on a cordon toll in a context requiring system efficiency, social equity and environmental quality. The optimized scheme yields an appreciable increase in social surplus through a relatively low rate compared to other similar pricing toll schemes. The results highlight the different considerations regarding mobility impacts on the case study area, as well as the major contributors to social welfare surplus. This leads the authors to reconsider the cost-analysis approach, as defined in the study, as the best option for formulating sustainability measures.

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In some countries, such as Spain, it is very common that in the same corridor there are two roads with the same origin and destination but with some differences. The most important contrast is that one is a toll highway which offers a better quality than the parallel road in exchange of a price. The users decide if the price of the toll is worth to pay for the advantages offered. This problem is known as the untolled alternative and it has been largely studied in the academic literature, particularly related to economic efficiency and the optimal welfare toll. However, there is a gap in the literature academic regarding how it affects income distribution to the optimal toll. The main objective of the paper is to fill this gap. In this paper a theoretical model in order to obtain the optimal welfare price in a toll highway that competes for capturing the traffic with a conventional road is developed. This model is done for non-usual users who decide over the expectation of free flow conditions. This model is finally applied to the variables we want to focus on: average value of travel time (VTT) which is strongly related with income, dispersion of this VTT and traffic levels, from free flow to congestion. Derived from the results, we conclude that the higher the average VTT the higher the optimal price, the higher the dispersion of this VTT the lower the optimal price and finally, the more the traffic the higher the optimal toll.

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This paper describes the design and application of the Atmospheric Evaluation and Research Integrated model for Spain (AERIS). Currently, AERIS can provide concentration profiles of NO2, O3, SO2, NH3, PM, as a response to emission variations of relevant sectors in Spain. Results are calculated using transfer matrices based on an air quality modelling system (AQMS) composed by the WRF (meteorology), SMOKE (emissions) and CMAQ (atmospheric-chemical processes) models. The AERIS outputs were statistically tested against the conventional AQMS and observations, revealing a good agreement in both cases. At the moment, integrated assessment in AERIS focuses only on the link between emissions and concentrations. The quantification of deposition, impacts (health, ecosystems) and costs will be introduced in the future. In conclusion, the main asset of AERIS is its accuracy in predicting air quality outcomes for different scenarios through a simple yet robust modelling framework, avoiding complex programming and long computing times.

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This paper explores the potential role of individual trip characteristics and social capital network variables in the choice of transport mode. A sample of around 100 individuals living or working in one suburb of Madrid (i.e. Las Rosas district of Madrid) participated in a smartphone short panel survey, entering travel data for an entire working week. A Mixed Logit model was estimated with this data to analyze shifts to metro as a consequence of the opening of two new stations in the area. Apart from classical explanatory variables, such as travel time and cost, gender, license and car ownership, the model incorporated two “social capital network” variables: participation in voluntary activities and receiving help for various tasks (i.e. child care, housekeeping, etc.). Both variables improved the capacity of the model to explain transport mode shifts. Further, our results confirm that the shift towards metro was higher in the case of people “helped” and lower for those participating in some voluntary activities.