July 18, 2024

On the tail behavior for randomly weighted sums of dependent random variables with its applications to risk measures

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ZCZhangting ChenChina Tourism Academy DCDongya ChengSoochow University

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Implication

Theoretical analysis demonstrates tail equivalence for randomly weighted sums of dependent random variables, highlighting improved asymptotic estimation for financial risk measures.

Key Points

Asymptotic tail equivalence holds for randomly weighted sums of dependent random variables across three heavy-tailed distribution classes, establishing predictable decay rates.
Theoretical modeling establishes closure properties when random weights satisfy bounded conditions alongside subexponential distributions with positive lower matuszewska indices.
Supports precise evaluation of portfolio risk measures under regularly varying distributions, while numerical simulations confirm the asymptotic accuracy of the derived bounds.

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Chen et al. (2024) studied this question.

synapsesocial.com/papers/68e5fee2b6db643587592396 https://doi.org/10.21203/rs.3.rs-4624067/v1

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Implication

Theoretical analysis demonstrates tail equivalence for randomly weighted sums of dependent random variables, highlighting improved asymptotic estimation for financial risk measures.

On the tail behavior for randomly weighted sums of dependent random variables with its applications to risk measures

Discussion

Member takes

Implication

Key Points

Cite This Study

On the tail behavior for randomly weighted sums of dependent random variables with its applications to risk measures

Discussion

Member takes

Implication

Key Points

Cite This Study

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