Consistent modeling of risk averse behavior with spectral risk measures

Wächter, Hans Peter; Mazzoni, Thomas

doi:10.1016/j.ejor.2013.03.001

Cited by 21 publications

(9 citation statements)

References 45 publications

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“…Wächter and Mazzoni (2013) have recently provided findings about the relation between utility framework and spectral risk measures. An important direction for future research is carrying on empirical studies by incorporating these findings in newsvendor experiments.…”

Section: Resultsmentioning

confidence: 98%

“…Spectral risk measures coincide with a class of utility functions of dual utility theory (Pflug, 2006). Wächter and Mazzoni (2013) have shown that it is possible to use spectral risk measures to model risk-averse behaviour of a decision maker whose preference relation is consistent with the dual theory of choice. Several risk measures such as CVaR and Mean-CVaR are special cases of spectral risk measures.…”

Section: Introductionmentioning

confidence: 97%

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The risk-averse newsvendor problem under spectral risk measures: A classification with extensions

Arıkan

Fichtinger

2017

European Journal of Operational Research

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Section: Resultsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 97%

The risk-averse newsvendor problem under spectral risk measures: A classification with extensions

Arıkan

Fichtinger

2017

European Journal of Operational Research

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“…Note that the theoretical validity of the above method is still unclear. Other methods to adequately construct SRMs from exponential utility functions have been discussed in [11,26,30], but no definite answer has been reached. In particular, it is pointed out in [11] that there exists no general consistency between expected utility theory and SRM-decision making.…”

Section: Example 2 Exponential/power Srmsmentioning

confidence: 99%

Asymptotic Analysis for Spectral Risk Measures Parameterized by Confidence Level

Kato¹

2017

SSRN Journal

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We study the asymptotic behavior of the difference ∆ρ X,Y α := ρ α (X + Y ) − ρ α (X) as α → 1, where ρ α is a risk measure equipped with a confidence level parameter 0 < α < 1, and where X and Y are non-negative random variables whose tail probability functions are regularly varying. The case where ρ α is the value-at-risk (VaR) at α, is treated in [20]. This paper investigates the case where ρ α is a spectral risk measure that converges to the worst-case risk measure as α → 1. We give the asymptotic behavior of the difference between the marginal risk contribution and the Euler contribution of Y to the portfolio X + Y . Similarly to [20], our results depend primarily on the relative magnitudes of the thicknesses of the tails of X and Y . We also conducted a numerical experiment, finding that when the tail of X is sufficiently thicker than that of Y , ∆ρ X,Y α does not increase monotonically with α and takes a maximum at a confidence level strictly less than 1.

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“…Note that the original parameter γ can be recovered using the inverse , and [20], but no definite answer has been reached.…”

Section: Preliminariesmentioning

confidence: 99%

Asymptotic Analysis for Spectral Risk Measures Parameterized by Confidence Level

Kato¹

2018

JMF

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Consistent modeling of risk averse behavior with spectral risk measures

Cited by 21 publications

References 45 publications

The risk-averse newsvendor problem under spectral risk measures: A classification with extensions

The risk-averse newsvendor problem under spectral risk measures: A classification with extensions

Asymptotic Analysis for Spectral Risk Measures Parameterized by Confidence Level

Asymptotic Analysis for Spectral Risk Measures Parameterized by Confidence Level

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