摘要翻译:
当决策者只有部分偏好信息时,可以使用最大熵原理来分配效用值。为了获得这样的效用值,有必要通过效用密度函数的概念在概率和效用之间建立类比。根据一些作者[Soofi(1990)、Abbas(2006a)(2006b)、Sandow et al.(2006)、Friedman and Sandow(2006)、Darooneh(2006)]的观点,最大熵效用解嵌入了一个庞大的效用函数族。本文利用最大熵原理来估计风险规避决策者的效用函数。
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英文标题:
《Utility function estimation: the entropy approach》
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作者:
Andreia Dionisio and A. Heitor Reis
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最新提交年份:
2007
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类:Physics 物理学
二级分类:Data Analysis, Statistics and Probability 数据分析、统计与概率
分类描述:Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件:数据处理与存储;测量方法;统计和数学方面,如参数化和不确定性。
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英文摘要:
The maximum entropy principle can be used to assign utility values when only partial information is available about the decision maker's preferences. In order to obtain such utility values it is necessary to establish an analogy between probability and utility through the notion of a utility density function. According to some authors [Soofi (1990), Abbas (2006a) (2006b), Sandow et al. (2006), Friedman and Sandow (2006), Darooneh (2006)] the maximum entropy utility solution embeds a large family of utility functions. In this paper we explore the maximum entropy principle to estimate the utility function of a risk averse decision maker.
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PDF链接:
https://arxiv.org/pdf/0709.0591