918 resultados para Capital assets pricing model


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A energia elétrica é fundamental para o desenvolvimento de qualquer país e o Brasil atravessa atualmente uma crise energética devido ao baixo nível de seus reservatórios, então diversos temas sobre o sistema elétrico brasileiro vêm à tona a fim de dar mais confiabilidade e evitar futuros racionamentos, permitindo assim que a escassez de energia não seja um impeditivo para o crescimento econômico do país. O presente estudo calcula o potencial de redução de demanda por energia elétrica no estado do Rio de Janeiro através do modelo de preço variável, que consiste em ter tarifas distintas para o horário de ponta e fora de ponta. Este é um entre diversos programas de eficiência energética existentes no mundo atualmente. Para tal cálculo as principais premissas são a projeção de demanda máxima coincidente, o número de consumidores por classe e a elasticidade preço da demanda por energia elétrica. A partir dai são sugeridos três cenários de penetração de AMI (Advanced Metering infrastructure), e três cenários de variação de preço, chegando assim a nove resultados possíveis.

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This paper studies the impact of (high rates) of infiation on ocupational choices in a model where the demand for labor is derived from a production technology that uses capital, productive labor, and managerial services done by administrative labor and money; while the supply of both kinds of labor is rigid in the short-run due to irreversible professional choices. The dynamic path of the economy after stabilization plans exhibits the main sty!ized facts reported in the literature inc1uding an initial consumption boon followed by a gradual adjustment. In its open economy version, the initial phase of the transitional dynamics exhibits capital infiight. The model also generates an increase of income inequality during the trasitional dynamics.

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In this paper a competi tive general equilibrium model is used to investigate the welfare and long run allocation impacts of privatization. There are two types of capital in this model economy, one private and the other initially public ("infrastructure"), and a positive extemality due to the latter is assumed. A benevolent governrnent can improve upon decentralized allocation intemalizing the extemality, but it introduces distortions in the economy through the finance of its investments. It is shown that even making the best case for public action - maximization of individuais' welfare, no operation inefficiency and free supply to society of infrastructure services - privatization is welfare improving for a large set of economies. Hence, arguments against privatization based solely on under-investment are incorrect, as this maybe the optimal action when the financing of public investment are considered. When operation inefficiency is introduced in the public sector, gains from privatization are much higher and positive for most reasonable combinations of parameters.

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We study an intertemporal asset pricing model in which a representative consumer maximizes expected utility derived from both the ratio of his consumption to some reference level and this level itself. If the reference consumption level is assumed to be determined by past consumption levels, the model generalizes the usual habit formation specifications. When the reference level growth rate is made dependent on the market portfolio return and on past consumption growth, the model mixes a consumption CAPM with habit formation together with the CAPM. It therefore provides, in an expected utility framework, a generalization of the non-expected recursive utility model of Epstein and Zin (1989). When we estimate this specification with aggregate per capita consumption, we obtain economically plausible values of the preference parameters, in contrast with the habit formation or the Epstein-Zin cases taken separately. All tests performed with various preference specifications confirm that the reference level enters significantly in the pricing kernel.

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In da Costa et al. (2006) we have shown how a same pricing kernel can account for the excess returns of the S&:P500 over the US short term bond and of the uncovered over the covered trading of foreign government bonds. In this paper we estimate and test the overidentifying restrictiom; of Euler equations associated with "ix different versions of the Consumption Capital Asset Pricing I\Iodel. Our main finding is that the same (however often unreasonable) values for the parameters are estimated for ali models in both nmrkets. In most cases, the rejections or otherwise of overidentifying restrictions occurs for the two markets, suggesting that success and failure stories for the equity premium repeat themselves in foreign exchange markets. Our results corroborate the findings in da Costa et al. (2006) that indicate a strong similarity between the behavior of excess returns in the two markets when modeled as risk premiums, providing empirical grounds to believe that the proposed preference-based solutions to puzzles in domestic financiaI markets can certainly shed light on the Forward Premium Puzzle.

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Peer-to-peer markets are highly uncertain environments due to the constant presence of shocks. As a consequence, sellers have to constantly adjust to these shocks. Dynamic Pricing is hard, especially for non-professional sellers. We study it in an accommodation rental marketplace, Airbnb. With scraped data from its website, we: 1) describe pricing patterns consistent with learning; 2) estimate a demand model and use it to simulate a dynamic pricing model. We simulate it under three scenarios: a) with learning; b) without learning; c) with full information. We have found that information is an important feature concerning rental markets. Furthermore, we have found that learning is important for hosts to improve their profits.

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The inventory management in hospitals is of paramount importance, since the supply materials and drugs interruption can cause irreparable damage to human lives while excess inventories involves immobilization of capital. Hospitals should use techniques of inventory management to perform replenishment in shorter and shorter intervals, in order to reduce inventories and fixed assets and meet citizens requirements properly. The inventory management can be an even bigger problem for public hospitals, which have restrictions on the use of resources and decisionmaking structure more bureaucratized. Currently the University Hospital Onofre Lopes (HUOL) uses a periodic replacement policy for hospital medical supplies and medicines, which involves one moment surplus stock replenishment, the next out of stock items. This study aims to propose a system for continuous replenishment through order point for inventory of medical supplies and medicines to the hospital HUOL. Therefore, a literature review of Federal University Hospitals Management, Logistics, Inventory Management and Replenishment System in Hospitals was performed, emphasizing the demand forecast, classification or ABC curve and order point system. And also, policies of inventory management and the current proposal were described, dealing with profile of the mentioned institution, the current policy of inventory management and simulation for continuous replenishment order point. For the simulation, the sample consisted of 102 and 44 items of medical and hospital drugs, respectively, selected using the ABC classification of inventory, prioritizing items of Class A, which contains the most relevant items in added value, representing 80 % of the financial value in 2012 fiscal year. Considering that it is a public organization, subject to the laws, we performed two simulations: the first, following the signs for inventory management of Instruction No. 205 (IN 205 ), from Secretary of Public Administration of the Presidency ( SEDAP / PR ), and the second, based on the literature specializing in inventory management hospital. The results of two simulations were compared to the current policy of replenishment system. Among these results are: an indication that the system for continuous replenishment reorder point based on IN 205 provides lower levels of safety stock and maximum stock, enables a 17% reduction in the amount spent for the full replenishment of inventories, in other words, decreasing capital assets, as well as reduction in stock quantity, also the simulation made from the literature has indicated parameters that prevent the application of this technique to all items of the sample. Hence, a change in inventory management of HUOL, with the application of the continuous replenishment according to IN 205, provides a significant reduction in acquisition costs of medical and hospital medicine

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Complex non-linear interactions between banks and assets we model by two time-dependent Erdos-Renyi network models where each node, representing a bank, can invest either to a single asset (model I) or multiple assets (model II). We use a dynamical network approach to evaluate the collective financial failure -systemic risk- quantified by the fraction of active nodes. The systemic risk can be calculated over any future time period, divided into sub-periods, where within each sub-period banks may contiguously fail due to links to either i) assets or ii) other banks, controlled by two parameters, probability of internal failure p and threshold T-h ("solvency" parameter). The systemic risk decreases with the average network degree faster when all assets are equally distributed across banks than if assets are randomly distributed. The more inactive banks each bank can sustain (smaller T-h), the smaller the systemic risk -for some Th values in I we report a discontinuity in systemic risk. When contiguous spreading becomes stochastic ii) controlled by probability p(2) -a condition for the bank to be solvent (active) is stochasticthe- systemic risk decreases with decreasing p(2). We analyse the asset allocation for the U.S. banks. Copyright (C) EPLA, 2014

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This study aims to develop innovative proposals for production agriculture management and plans to build a participatory model, through the digital inclusion of members of the family farm gathered in a cooperative venture seeking to establish new environmental management efficiency for household production. The first part of the hypothesis assumes that a major obstacle to the insertion of small family farms into the markets is skilled labor, human capital. A training model has been developed for traceability and tracking activities on family farms, based on the atemoya culture. The second hypothesis predicts that it is possible to create a model that is scientifically supported by widely accepted rules derived from GlobalGAP standard certification, a global benchmark for good agricultural practices. Using these rules the model seeks to achieve the traceability of agricultural products and operations from the preservation of identity information within the production chain. The results obtained by the computerized system confirmed the presented hypotheses by demonstrating that technological innovation through intensive communication and information technologies education as well as other associated forms are important drivers of regional development, especially if implemented through a digital inclusion project using the state program Infocentros Access São Paulo.

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Real Options Analysis (ROA) has become a complimentary tool for engineering economics. It has become popular due to the limitations of conventional engineering valuation methods; specifically, the assumptions of uncertainty. Industry is seeking to quantify the value of engineering investments with uncertainty. One problem with conventional tools are that they may assume that cash flows are certain, therefore minimizing the possibility of the uncertainty of future values. Real options analysis provides a solution to this problem, but has been used sparingly by practitioners. This paper seeks to provide a new model, referred to as the Beta Distribution Real Options Pricing Model (BDROP), which addresses these limitations and can be easily used by practitioners. The positive attributes of this new model include unconstrained market assumptions, robust representation of the underlying asset‟s uncertainty, and an uncomplicated methodology. This research demonstrates the use of the model to evaluate the use of automation for inventory control.

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The United States disposes roughly 60% of the municipal solid waste it generates each year in solid waste disposal facilities, commonly known as landfills. Hedonic pricing studies have estimated the external costs of landfills on neighboring housing markets, but the literature is silent on what happens to property values after the landfill closes. Original housing price data collected both before and after a landfill closure are used to estimate how a landfill closure affects neighboring property values. Results of both a hedonic pricing model and repeat-sales estimator are used in the analysis.

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Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

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Experts working on behalf of international development organisations need better tools to assist land managers in developing countriesmaintain their livelihoods, as climate change puts pressure on the ecosystemservices that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories andmethods. This reviewtherefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change,whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change.

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Between 2004 and 2007, NGOs, community based organisations and private investors promoted jatropha in Kenya with the aim of generating additional income and producing biofuel for rural development. By 2008 it became gradually evident that jatropha plantations (both mono- and intercropping) are uneconomical and risky due to competition for land and labour with food crops. Cultivation of jatropha hedges was found to have better chances of economic success and to present only little risks for the adopting farmers. Still, after 2008 a number of farmers went on adopting jatropha in plots rather than as hedges. It is hypothesised that lack of awareness about the low economic prospects of jatropha plantations was the main reason for continued adoption, and that smallholder farmers with higher resource endowments mainly ventured into its cultivation. In this study we provide an empirical basis for understanding the role of households' capital assets in taking up new livelihood strategies by smallholder farmers in three rural districts in Kenya. For that purpose, we assess the motivation and enabling factors that led to the adoption of jatropha as a new livelihood strategy, as well as the context in which promotion and adoption took place. A household survey was conducted in 2010, using a structured questionnaire, to collect information on household characteristics and capital asset endowment. Data were analysed using descriptive statistics and non-parametric statistical tests. We established that access to additional income and own energy supply were the main motivation for adoption of jatropha, and that financial capital assets do not necessarily have a positive influence on adoption as hypothesised. Further, we found that the main challenges that adopting farmers faced were lack of access to information on good management practices and lack of a reliable market. We conclude that continued adoption of on-farm jatropha after 2008 is a result of lacking awareness about the low economic value of this production type. We recommend abandoning on-farm production of jatropha until improved seed material and locally adapted agronomic knowledge about jatropha cultivation becomes available and its production becomes economically competitive.