A Tail Measure With Variable Risk Tolerance: Application in Dynamic Portfolio Insurance Strategy

Hu, Wentao; Chen, Cuixia; Shi, Yufeng; Chen, Ze

doi:10.1007/s11009-022-09951-4

Cited by 4 publications

(2 citation statements)

References 65 publications

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“…Yaari [18]). As an example, for some recent applications see Hu et al [19] (in risk theory), and Navarro [20] and Navarro et al [21] (in statistics). (i) If the cumulative weight function is given by ψ(x) = F 0 (x), then due to (8) the WMIT function of X can be expressed as…”

Section: Weighted Mean Inactivity Time Functionmentioning

confidence: 99%

Weighted Mean Inactivity Time Function with Applications

Crescenzo

Toomaj

2022

Mathematics

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We consider an extension of the mean inactivity time based on a non-negative weight function. We show various properties of the new notion, and relate it to various functions of interest in reliability theory and information measures, such as the dynamic cumulative entropy, the past entropy, the varentropy, and the weighted cumulative entropy. Moreover, based on the comparison of weighted mean inactivity times, we introduce and study a new stochastic order and compare it with other suitable orders. We also discuss some results about the variance of transformed random variables and the weighted generalized cumulative entropy. Then, we investigate certain connections with the location-independent riskier order. Finally, we pinpoint several characterizations and preservation properties of the new stochastic order under shock models, random maxima, and notions of renewal theory.

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Section: Weighted Mean Inactivity Time Functionmentioning

confidence: 99%

Weighted Mean Inactivity Time Function with Applications

Crescenzo

Toomaj

2022

Mathematics

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“…Hence, both risk measures serve complementary goals and practical priorities should guide which one is most appropriate to use. In the portfolio management literature this kind of trade-off between the ES and VaR is known and has resulted in the development of a risk measure which is a convex combination based on risk preferences [48]. Comparing and choosing risk measures based on statistical robustness is to our knowledge a rather novel approach in the systemic risk literature.…”

Section: Introductionmentioning

confidence: 99%

$Δ-$CoES

Aleksy¹

2022

Preprint

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In this paper the ∆-CoVaR method is extended in both the conditional and unconditional cases to be based on the Expected Shortfall (ES) using quantile regression with a more expansive distress definition. We find the resulting ∆-CoES measure to be complementary to the ∆-CoVaR and to be more effective than the ∆-CoVaR in measuring short-term changes in systemic risk and in identifying heterogeneity in the systemic risk contributions of financial institutions and linkages between institutions due to its lower robustness. For regulators, risk managers and market participants these properties are interesting from an economic standpoint when they require the increased sensitivity and heterogeneity of the ∆-CoES to set short-term capital requirements/risk limits, find problematic financial linkages, problematic financial institutions or have some kind of early warning system for the emergence of systemic risk. Lastly, the ∆-CoES is straightforward to estimate and would fit within recent regulatory frameworks such as the FRTB. To show the statistical advantages and properties empirically, the ∆-CoVaR and ∆-CoES methods are used on a large sample (from 31-12-1970 to 31-12-2020 1564 firms) of daily equity data from US financial institutions both in a system and network fashion. On a sample of 9 US-based GSIBS we also show the properties and the utility of the ∆-CoES when it comes to identifying problematic financial links.

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Monotone tail functions: Definitions, properties, and application to risk-reducing strategies

Hanbali

Linders

2022

Journal of Computational and Applied Mathematics

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A Tail Measure With Variable Risk Tolerance: Application in Dynamic Portfolio Insurance Strategy

Cited by 4 publications

References 65 publications

Weighted Mean Inactivity Time Function with Applications

Weighted Mean Inactivity Time Function with Applications

$Δ-$CoES

Monotone tail functions: Definitions, properties, and application to risk-reducing strategies

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