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Application of the Mean-Variance Theory and Resampling Technique for the Italian energy portfolio settlement

机译:平均方差理论与重采样技术在意大利能源组合沉降中的应用

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The energy planning based on Mean - Variance theory, guides the investors in investment decisions, trying to maximize the return and minimize the risk of investment. However, this theory is based on strong hypotheses and, in addition, input data are often affected by estimation errors. Moreover, this theory determines poor diversification increasing return and risk of the portfolio, and strong variability of the outputs when inputs are varied. In the first part of the paper, the Mean - Variance theory was applied to the energy generation in Italy; in particular, the analysis was on the actual energy mix, but also assuming the use of nuclear technology and taking into account verisimilar improvement, of technologies in the future. On the other hand, in the second part of the paper, a methodology has been applied in order to limit the problems of Mean-Variance theory applied to the energy mix settlement. In particular, the input variables have been calculated using Monte Carlo simulation, in order to reduce the estimation error, and the Resampled Efficiency ? technique has been applied in order to calculate the resulting new "average" efficient frontier. This methodology has been applied either not limiting or limiting the minimum and maximum percentage for every energy generation technology, in order to simulate constraints due, for example, to the technological characteristics of the plant, the availability of the sources and eventually to norms, to the territorial characteristics and to the socio-political choices. The application of Mean - Variance theory allowed to obtain energy portfolio, alternative to the actual, characterized by higher values of expected returns an lower values of risk. It was also shown that the application of the Resampled Efficiency ? technique with data originated with the Monte Carlo simulation effectively tackles the problems of Mean - Variance theory; in this way, the decision maker is helped in making decisions in the energy system policy and development. Thanks to this approach, applied in particular to the Italian energy contest, it was also possible to evaluate the effectiveness of the introduced modifications to the Italian actual energy mix to achieve the 2020 European Energy Directive targets in particular concerning the reduction of CO_2 levels.
机译:基于均值能源规划 - 方差理论,指导投资决策的投资者,试图最大限度的回报,尽可能减少投资的风险。然而,这个理论是建立在强大的假设,此外,输入数据往往受估计误差。此外,这一理论决定了可怜的多元化增加收益和投资组合的风险,而当输入改变输出的可变性强。在本文的第一部分,均值 - 方差理论应用于意大利能源发电;特别是,分析是在实际的能源结构,而且假设使用核技术,并在未来考虑到逼真的改进,技术。在另一方面,在论文的第二部分,方法已在以限制应用到能源结构解决均值 - 方差理论问题中的应用。特别是,输入变量已经利用蒙特卡罗模拟,以减少估计误差被计算出来,并重新采样的效率?技术已经在为了计算得到的新的“平均”有效前沿得到应用。这种方法已经应用于要么没有限制或限制每个发电技术的最小和最大百分比,以模拟限制由于例如,植物,来源可用性的技术特点,并最终规范,领土的特点和对社会和政治选择。平均的应用 - 方差理论允许获得能源组合,替代实际的,其特点是预期收益风险的较低值的较高值。它也表明,重采样效率的应用程序?数据起源于蒙特卡罗模拟技术有效地铲球平均的问题 - 方差理论;这样,决策者在做能源系统的政策和发展的决策有帮助。由于这种方法,特别适用于意大利能源竞赛,它也可能将推出改进的有效性评估意大利的实际能源结构,实现2020年欧盟能源指令的目标特别是关于CO_2水平的降低。

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