8 resultados para Constant Relative Risk Aversion

em Repositório Científico do Instituto Politécnico de Lisboa - Portugal


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In this paper, a mixed-integer nonlinear approach is proposed to support decision-making for a hydro power producer, considering a head-dependent hydro chain. The aim is to maximize the profit of the hydro power producer from selling energy into the electric market. As a new contribution to earlier studies, a risk aversion criterion is taken into account, as well as head-dependency. The volatility of the expected profit is limited through the conditional value-at-risk (CVaR). The proposed approach has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems.

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In this paper, a mixed-integer quadratic programming approach is proposed for the short-term hydro scheduling problem, considering head-dependency, discontinuous operating regions and discharge ramping constraints. As new contributions to earlier studies, market uncertainty is introduced in the model via price scenarios, and risk aversion is also incorporated by limiting the volatility of the expected profit through the conditional value-at-risk. Our approach has been applied successfully to solve a case Study based on one of the main Portuguese cascaded hydro systems, requiring a negligible computational time.

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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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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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This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

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Mestrado em Contabilidade e Gestão das Instituições Financeiras

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Anaemia has a significant impact on child development and mortality and is a severe public health problem in most countries in sub-Saharan Africa. Nutritional and infectious causes of anaemia are geographically variable and anaemia maps based on information on the major aetiologies of anaemia are important for identifying communities most in need and the relative contribution of major causes. We investigated the consistency between ecological and individual-level approaches to anaemia mapping, by building spatial anaemia models for children aged ≤15 years using different modeling approaches. We aimed to a) quantify the role of malnutrition, malaria, Schistosoma haematobium and soil-transmitted helminths (STH) for anaemia endemicity in children aged ≤15 years and b) develop a high resolution predictive risk map of anaemia for the municipality of Dande in Northern Angola. We used parasitological survey data on children aged ≤15 years to build Bayesian geostatistical models of malaria (PfPR≤15), S. haematobium, Ascaris lumbricoides and Trichuris trichiura and predict small-scale spatial variation in these infections. The predictions and their associated uncertainty were used as inputs for a model of anemia prevalence to predict small-scale spatial variation of anaemia. Stunting, PfPR≤15, and S. haematobium infections were significantly associated with anaemia risk. An estimated 12.5%, 15.6%, and 9.8%, of anaemia cases could be averted by treating malnutrition, malaria, S. haematobium, respectively. Spatial clusters of high risk of anaemia (>86%) were identified. Using an individual-level approach to anaemia mapping at a small spatial scale, we found that anaemia in children aged ≤15 years is highly heterogeneous and that malnutrition and parasitic infections are important contributors to the spatial variation in anemia risk. The results presented in this study can help inform the integration of the current provincial malaria control program with ancillary micronutrient supplementation and control of neglected tropical diseases, such as urogenital schistosomiasis and STH infection.

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The Cultural Property Risk Analysis Model was applied in 2006 to a Portuguese archive located in Lisbon. Its results highlighted the need for the institution to take care of risks related to fire, physical forces and relative humidity problems. Five years after this first analysis the results are revisited and a few changes are introduced due to recent events: fire and high humidity remain an important hazard but are now accompanied by a pressing contaminants problem. Improvements in storage systems were responsible for a large decrease in terms of calculated risk magnitude and proved to be very cost-effective.