• Corpus ID: 255546289

Diversification quotients based on VaR and ES

@inproceedings{Han2023DiversificationQB,
  title={Diversification quotients based on VaR and ES},
  author={Xia Han and Liyuan Lin and Ruodu Wang},
  year={2023}
}
The diversification quotient (DQ) is a recently introduced tool for quantifying the degree of diversification of a stochastic portfolio model. It has an axiomatic foundation and can be defined through a parametric class of risk measures. Since the Value-at-Risk (VaR) and the Expected Shortfall (ES) are the most prominent risk measures widely used in both banking and insurance, we investigate DQ constructed from VaR and ES in this paper. In particular, for the popular models of elliptical and… 

Figures and Tables from this paper

Diversification Quotients: Quantifying Diversification via Risk Measures

We establish the first axiomatic theory for diversification indices using six intuitive axioms – non-negativity, location invariance, scale invariance, rationality, normalization, and continuity –

References

SHOWING 1-10 OF 37 REFERENCES

PELVE: Probability Equivalent Level of VaR and ES

In the recent Fundamental Review of the Trading Book (FRTB), the Basel Committee on Banking Supervision proposed the shift from the 99% Value-at-Risk (VaR) to the 97.5% Expected Shortfall (ES) for

On optimal portfolio diversification with respect to extreme risks

Strong consistency and asymptotic normality are established for a semiparametric estimator of the mapping ξ↦γξ and strong consistency is also established for the estimated optimal portfolio.

Asymptotic analysis of portfolio diversification

Risk Aggregation, Dependence Structure and Diversification Benefit

Insurance and reinsurance live and die from the diversification benefits or lack of it in their risk portfolio. The new solvency regulations allow companies to include them in their computation of

Toward Maximum Diversification

Along with the ongoing effort to build market cap–independent portfolios, the authors explore the properties of diversification as a driver of portfolio construction. They introduce a measure of the

Diversification in heavy-tailed portfolios: properties and pitfalls

Abstract We discuss risk diversification in multivariate regularly varying models and provide explicit formulas for Value-at-Risk asymptotics in this case. These results allow us to study the

Diversification limit of quantiles under dependence uncertainty

In this paper, we investigate the asymptotic behavior of the portfolio diversification ratio based on Value-at-Risk (quantile) under dependence uncertainty, which we refer to as “worst-case

COHERENCE AND ELICITABILITY

The existing result of the nonelicitability of expected shortfall is extended to all law-invariant spectral risk measures unless they reduce to minus the expected value.

Quantile-Based Risk Sharing

It is shown that, in general, a robust optimal allocation exists if and only if none of the underlying risk measures is a VaR, and several novel advantages of ES over VaR from the perspective of a regulator are revealed.

Generalized Quantiles as Risk Measures

In the statistical and actuarial literature several generalizations of quantiles have been considered, by means of the minimization of a suitable asymmetric loss function. All these generalized