1,721,121 research outputs found
On the relationship between comparisons of risk aversion of different orders
No full textWe show conditions which ensure that the comparisons between risk aversion of different orders of two decision makers are related. In particular, we derive a condition ensuring that greater downside risk aversion implies greater risk aversion and a different condition ensuring that the opposite implication holds. We then generalize these results to higher order greater risk aversion, obtaining conditions which make it possible to infer the direction of the comparison for risk aversion of a given order from the knowledge of the direction for a different order. (c) 2022 Elsevier B.V. All rights reserved
Changes in multiplicative risks and optimal portfolio choice: new interpretations and results
No full textThis paper reconsiders the conditions determining the optimal response of a decision maker in case of stochastic changes in multiplicative risks. In particular, we focus on an optimal portfolio choice where the return of the risky asset exhibits an Nth-degree risk increase. We provide two interpretations of the conditions analyzed. The first interpretation involves a comparison between the elasticities with respect to the investment in the risky asset of the Nth derivative of the utility function and of the distance between the Nth moments of the two risks. The second interpretation refers to the direction of the change in the utility premium when the investment in the risky asset changes. We then study the linkages between the conditions determining optimal responses of risky investment in the case of risk increases of different degrees. We show that, under some assumptions, the optimal behavior of an agent in the case of Nth degree risk increase makes it possible to infer agent’s behavior in case of risk increases of lower degrees
DGFLOW: a software for energy folw analysis of distribution systems with distributed generation
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Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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