The Efficiency Analysis of Choices Involving Risk

Hanoch, Giora; Levy, Haim

doi:10.2307/2296431

Cited by 1,154 publications

(345 citation statements)

References 16 publications

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“…The concept was previously applied to compare distributions of investment portfolio returns in financial valuation studies (Hanoch andLevy 1969, Rothschild andStiglitz 1970) and shares many technical aspects with the partial ordering of vectors and majorization theory in statistics (Whitemore andFindlay 1978, Levy 1992). The SD rule compares two distributions based on their cumulative distribution functions, or CDFs (Levy 1998).…”

Section: Stochastic Dominance (Sd) Rulementioning

confidence: 99%

Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker’s perspective

Yemshanov¹,

Koch²,

Ducey³

et al. 2013

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Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker.We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first-and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. NeoBiotaDenys Yemshanov et al. / NeoBiota 18: 193-218 (2013) 194While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada.

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Section: Stochastic Dominance (Sd) Rulementioning

confidence: 99%

Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker’s perspective

Yemshanov¹,

Koch²,

Ducey³

et al. 2013

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“…[15] demonstrated that if the ordering of alternatives is to satisfy the NM (Von Neumann-Morgenstern, [16]) axioms of rational behavior, only a quadratic NM utility function is consistent with an ordinal expected utility function that depends solely on the mean and variance of the return. Thereafter, [17] formulated an efficient set of definitions corresponding to the quadratic utility assumption. [18] pointed out that even if the return for each alternative has a normal distribution, the mean-variance framework cannot be used to rank alternatives consistent with the NM axioms unless a quadratic utility function is used.…”

Section: Stochastic Dominance and Mean-variance Approachmentioning

confidence: 99%

Banking Firm, Risk of Investment and Derivatives

Бролл¹,

Wong²,

Wu³

2011

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The economic environment for financial institutions has become increasingly risky. Hence these institutions must find ways to manage risk of which one of the most important forms is credit risk. In this paper we use the mean-variance (mean-standard deviation) approach to examine a banking firm investing in risky assets and hedging opportunities. The mean-standard deviation framework can be used because our hedging model satisfies a scale and location condition. The focus of this study is on how credit risk affects optimal bank investment in the loan and deposit market when derivatives are available. Furthermore we explore the relationship among the first-and second-degree stochastic dominance efficient sets and the mean-variance efficient set.

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“…In an effort to overcome the shortcomings 1 of the previous methods, the second order stochastic dominance (SSD) was invented by Hanoch and Levy (1969). In essence, their method makes it possible to evaluate just a single portfolio by SSD efficiency with the help of pairwise comparisons of all belonging assets.…”

Section: Introductionmentioning

confidence: 99%

SSD Efficiency at Multiple Data Frequencies: Application on the OECD Countries

Uğurlu¹,

Taş²,

Güran³

et al. 2018

Prague Economic Papers

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The second order stochastic dominance (SSD) has become exceedingly popular in recent years, due to its ability to determine the dominance of one asset over another for all risk-averse investors without a strict requirement in asset distribution. In this study, 33 OECD country indexes and their enriched set of assets, which consists of some combinations of these indexes, are investigated and compared between 2007 and 2015 by utilizing pairwise SSD comparisons, with different data frequencies, such as daily, weekly, monthly and quarterly. This paper contributes to the literature in three points: Firstly, a serious portion of the best performing OECD countries has the lowest GDP (PPP) per capita level. Secondly, the SSD efficient set depends on data frequency. Thirdly, when the data frequency is lowered, the difference between two SSD pairwise efficiency tests decreases.

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The Efficiency Analysis of Choices Involving Risk

Cited by 1,154 publications

References 16 publications

Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker’s perspective

Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker’s perspective

Banking Firm, Risk of Investment and Derivatives

SSD Efficiency at Multiple Data Frequencies: Application on the OECD Countries

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