Closed-form solutions for worst-case law invariant risk measures with application to robust portfolio optimization

TL;DR

This paper derives closed-form solutions for worst-case law invariant risk measures, extending known results for VaR and CVaR, and applies these findings to robust portfolio optimization.

Contribution

It introduces new closed-form solutions for a broad class of worst-case risk measures, linking them to existing measures like VaR and CVaR for improved portfolio optimization.

Findings

Closed-form solutions for worst-case law invariant risk measures.

Connection established between worst-case law invariant measures and CVaR.

Application to robust portfolio optimization demonstrated.

Abstract

Worst-case risk measures refer to the calculation of the largest value for risk measures when only partial information of the underlying distribution is available. For the popular risk measures such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), it is now known that their worst-case counterparts can be evaluated in closed form when only the first two moments are known for the underlying distribution. These results are remarkable since they not only simplify the use of worst-case risk measures but also provide great insight into the connection between the worst-case risk measures and existing risk measures. We show in this paper that somewhat surprisingly similar closed-form solutions also exist for the general class of law invariant coherent risk measures, which consists of spectral risk measures as special cases that are arguably the most important extensions of CVaR. We shed light on the one-to-one correspondence between a worst-case law invariant risk measure and a worst-case CVaR (and a worst-case VaR), which enables one to carry over the development of worst-case VaR in the context of portfolio optimization to the worst-case law invariant risk measures immediately.