837 resultados para Pricing.


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OBJECTIVE:

To study the postoperative visual function and uptake of refraction and second-eye surgery among persons undergoing cataract surgery in rural China.

METHODS:

Self-reported visual function was measured 10 to 14 months after surgery. Subjects with improvement of 2 or more lines with refraction were offered glasses, and those with significant cataract were offered second-eye surgery.

RESULTS:

Among 313 eligible subjects, 242 (77%) could be contacted; 176 (73%) of those contacted were examined. Interviewed subjects had a mean +/- SD age of 69.9 +/- 10.2 years, and 63.6% were female. The mean +/- SD visual function score was 88.4 +/- 12.3, higher than previously reported for cataract programs in rural China and significantly (P = .03) correlated with presenting vision. Forty-two percent of subjects had spectacles, more than half being reading glasses. Though 87% of subjects' vision improved with refraction, only 35% accepted prescriptions, the most common reason for refusal being lack of perceived need. Second-eye surgery was accepted by a total of 48% (85 of 176) of patients, cost being the biggest reason for refusal.

CONCLUSIONS:

Visual function was high in this cohort. Potential benefit of refraction and second-eye surgery was substantial, but uptake of services was modest. Programs to improve service uptake should focus on reading glasses and cost-reduction strategies such as tiered pricing.

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By testing a simple asset pricing model of heterogeneous agents to characterize the power-law behavior of the DAX 30 from 1975 to 2007, we provide supporting evidence on empirical findings that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. By conducting econometric analysis via Monte Carlo simulations, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely the corresponding estimates for the DAX 30. A mechanism analysis based on the calibrated model provides further insights into the explanatory power of heterogeneous agent models.

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Sempre foi do interesse das instituições financeiras de crédito determinar o risco de incumprimento associado a uma empresa por forma a avaliar o seu perfil. No entanto, esta informação é útil a todos os stakeholders de uma empresa, já que também estes comprometem uma parte de si ao interagirem com esta. O aumento do número de insolvências nos últimos anos tem reafirmado a necessidade de ampliar e aprofundar a pesquisa sobre o stress financeiro. A identificação dos fatores que influenciam a determinação do preço dos ativos sempre foi do interesse de todos os stakeholders, por forma a antecipar a variação dos retornos e agir em sua conformidade. Nesta dissertação será estudada a influência do risco de incumprimento sobre os retornos de capital, usando como indicador do risco de incumprimento a probabilidade de incumprimento obtida segundo o modelo de opções de Merton (1974). Efetuou-se esta análise durante o período de Fevereiro de 2002 a Dezembro de 2011, utilizando dados de empresas Portuguesas, Espanholas e Gregas. Os resultados evidenciam uma relação negativa do risco de incumprimento com os retornos de capital, que é devida a um efeito momentum e à volatilidade. A par disso, também se demonstra que o tamanho e o book-to-market não são representativos do risco de incumprimento na amostra aqui utilizada, ao contrário do que Fama & French (1992; 1996) afirmavam.

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We generalize the concept of .systematic risk to a broad class of risk measures potentially accounting for high distribution moments, downside risk, rare disasters, as well as other risk attributes. We offer two different approaches. First is an equilibrium framework generalizing the Capital Asset Pricing Model, two-fund separation, and the security market line. Second is an axiomatic approach resulting in a systematic risk measure as the unique solution to a risk allocation problem. Both approaches lead to similar results extending the traditional beta to capture multiple dimensions of risk. The results lend themselves naturally to empirical investigation.

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Thesis (Ph.D.)--University of Washington, 2013

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Christoph Franz of Lufthansa recently identified Ryanair, easyJet, Air Berlin and Emirates as the company’s main competitors – gone are the days when it could benchmark itself against BA or Air France-KLM! This paper probes behind the headlines to assess the extent to which different airlines are in competition, using evidence from the UK and mainland European markets. The issue of route versus network competition is addressed. Many regulators have put an emphasis on the former whereas the latter, although less obvious, can be more relevant. For example, BA and American will cease to compete between London and Dallas Fort Worth if their alliance obtains anti-trust immunity but 80% of the passengers on this route are connecting at one or both ends and hence arguably belong to different markets (e.g. London-San Francisco, Zurich-Dallas, Edinburgh-New Orleans) which may be highly contested. The remaining 20% of local traffic is actually insufficient to support a single point to point service in its own right. Estimates are made of the seat capacity major airlines are offering to the local market as distinct from feeding other routes. On a sector such as Manchester–Amsterdam, 60% of KLM’s passengers are transferring at Schiphol as against only 1% of bmibaby’s. Thus although KLM operates 5 flights and 630 seats per day against bmibaby’s 2 flights and 298 seats, in the point to point market bmibaby offers more seats than KLM. The growth of the Low Cost Carriers (LCCs) means that competition increasingly needs to be viewed on city pair markets (e.g. London-Rome) rather than airport pair markets (e.g. Heathrow-Fiumicino). As the stronger LCCs drive out weaker rivals and mainline carriers retrench to their major hubs, some markets now have fewer direct options than existed prior to the low cost boom. Timings and frequencies are considered, in particular the extent to which services are a true alternative especially for business travellers. LCCs typically offer lower frequencies and more unsociable timings (e.g. late evening arrivals at remote airports) as they are more focused on providing the cheapest service rather than the most convenient schedule. Interesting findings on ‘monopoly’ services are presented (including alliances) - certain airlines have many more of these than others. Lufthansa has a significant number of sectors to itself whereas at the other extreme British Airways has direct competition on almost every route in its network. Ryanair and flybe have a higher proportion of monopoly routes than easyJet or Air Berlin. In the domestic US market it has become apparent since deregulation that better financial returns can come from dominating a large number of smaller markets rather than being heavily exposed in the major markets - which are hotly fought over. Regional niches that appear too thin for Ryanair to serve (with its all 189 seat 737-800 fleet) are identified. Fare comparisons in contrasting markets provide some insights to marketing and pricing strategies. Data sources used include OAG (schedules and capacity), AEA (traditional European airlines traffic by region), the UK CAA (airport, airline and route traffic plus survey information of passenger types) and ICAO (international route traffic and capacity by carrier). It is concluded that airlines often have different competitors depending on the context but in surprisingly many cases there are actually few or no direct substitutes. The competitive process set in train by deregulation of European air services in the 1990s is leading back to one of natural monopolies and oblique alternatives. It is the names of the main participants that have changed however!

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This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

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Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

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In smart grids context, the distributed generation units based in renewable resources, play an important rule. The photovoltaic solar units are a technology in evolution and their prices decrease significantly in recent years due to the high penetration of this technology in the low voltage and medium voltage networks supported by governmental policies and incentives. This paper proposes a methodology to determine the maximum penetration of photovoltaic units in a distribution network. The paper presents a case study, with four different scenarios, that considers a 32-bus medium voltage distribution network and the inclusion storage units.

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This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.

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In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

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A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

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Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do obtenção do grau de Mestre em Auditoria Auditoria, sob orientação de Adalmiro Álvaro Malheiro de Castro Andrade

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Ramsey pricing has been proposed in the pharmaceutical industry as a principle to price discriminate among markets while allowing to recover the (fixed) R&D cost. However, such analyses neglect the presence of insurance or the fund raising costs for most of drug reimbursement. By incorporating these new elements, we aim at providing some building blocks towards an economic theory incorporating Ramsey pricing and insurance coverage. We show how coinsurance affects the optimal prices to pay for the R&D investment. We also show that under certain conditions, there is no strategic incentive by governments to set coinsurance rates in order to shift the financial burden of R&D. This will have important implications to the application of Ramsey pricing principles to pharmaceutical products across countries.

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Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Auditoria, sob orientação da Mestre Gabriela Pinheiro