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Relevant bibliographies by topics / Law Invariant Risk Measures

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Academic literature on the topic 'Law Invariant Risk Measures'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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Journal articles on the topic "Law Invariant Risk Measures"

1

Ekeland, Ivar, та Walter Schachermayer. "Law invariant risk measures onL∞(ℝd)". Statistics & Risk Modeling 28, № 3 (2011): 195–225. http://dx.doi.org/10.1524/stnd.2011.1099.

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2

Cherny, Alexander S., and Pavel G. Grigoriev. "Dilatation monotone risk measures are law invariant." Finance and Stochastics 11, no. 2 (2007): 291–98. http://dx.doi.org/10.1007/s00780-007-0034-8.

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3

Lacker, Daniel. "Law invariant risk measures and information divergences." Dependence Modeling 6, no. 1 (2018): 228–58. http://dx.doi.org/10.1515/demo-2018-0014.

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AbstractAone-to-one correspondence is drawnbetween lawinvariant risk measures and divergences,which we define as functionals of pairs of probability measures on arbitrary standard Borel spaces satisfying a few natural properties. Divergences include many classical information divergence measures, such as relative entropy and convex f -divergences. Several properties of divergence and their duality with law invariant risk measures are characterized, such as joint semicontinuity and convexity, and we notably relate their chain rules or additivity properties with certain notions of time consisten

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4

Chen, Shengzhong, Niushan Gao, and Foivos Xanthos. "The strong Fatou property of risk measures." Dependence Modeling 6, no. 1 (2018): 183–96. http://dx.doi.org/10.1515/demo-2018-0012.

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AbstractIn this paper, we explore several Fatou-type properties of risk measures. The paper continues to reveal that the strong Fatou property,whichwas introduced in [19], seems to be most suitable to ensure nice dual representations of risk measures. Our main result asserts that every quasiconvex law-invariant functional on a rearrangement invariant space X with the strong Fatou property is (X, L1) lower semicontinuous and that the converse is true on a wide range of rearrangement invariant spaces. We also study inf-convolutions of law-invariant or surplus-invariant risk measures that preserv

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5

Chen, Shengzhong, Niushan Gao, Denny H. Leung, and Lei Li. "Automatic Fatou property of law-invariant risk measures." Insurance: Mathematics and Economics 105 (July 2022): 41–53. http://dx.doi.org/10.1016/j.insmatheco.2022.03.007.

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6

Cheung, K. C., K. C. J. Sung, S. C. P. Yam, and S. P. Yung. "Optimal reinsurance under general law-invariant risk measures." Scandinavian Actuarial Journal 2014, no. 1 (2011): 72–91. http://dx.doi.org/10.1080/03461238.2011.636880.

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7

Xin, Linwei, and Alexander Shapiro. "Bounds for nested law invariant coherent risk measures." Operations Research Letters 40, no. 6 (2012): 431–35. http://dx.doi.org/10.1016/j.orl.2012.09.002.

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8

Shapiro, Alexander. "On Kusuoka Representation of Law Invariant Risk Measures." Mathematics of Operations Research 38, no. 1 (2013): 142–52. http://dx.doi.org/10.1287/moor.1120.0563.

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9

CHEN, YANHONG, and YIJUN HU. "SET-VALUED LAW INVARIANT COHERENT AND CONVEX RISK MEASURES." International Journal of Theoretical and Applied Finance 22, no. 03 (2019): 1950004. http://dx.doi.org/10.1142/s0219024919500043.

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In this paper, we investigate representation results for set-valued law invariant coherent and convex risk measures, which can be considered as a set-valued extension of the multivariate scalar law invariant coherent and convex risk measures studied in the literature. We further introduce a new class of set-valued risk measures, named set-valued distortion risk measures, which can be considered as a set-valued version of multivariate scalar distortion risk measures introduced in the literature. The relationship between set-valued distortion risk measures and set-valued weighted value at risk i

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10

Belomestny, Denis, and Volker Krätschmer. "Central Limit Theorems for Law-Invariant Coherent Risk Measures." Journal of Applied Probability 49, no. 1 (2012): 1–21. http://dx.doi.org/10.1239/jap/1331216831.

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In this paper we study the asymptotic properties of the canonical plugin estimates for law-invariant coherent risk measures. Under rather mild conditions not relying on the explicit representation of the risk measure under consideration, we first prove a central limit theorem for independent and identically distributed data, and then extend it to the case of weakly dependent data. Finally, a number of illustrating examples is presented.

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