# Spectral risk measures and uncertainty

## TL;DR

This paper enhances risk assessment by adapting spectral risk measures within a robust framework and introduces a deviation-based method to quantify uncertainty, demonstrated through a NASDAQ index case study.

## Contribution

It proposes a novel robust framework for spectral risk measures and a deviation-based approach to quantify uncertainty in risk assessment.

## Key findings

- Robust spectral risk measures improve risk evaluation.
- Deviation-based uncertainty quantification provides new insights.
- Application to NASDAQ index illustrates practical utility.

## Abstract

Risk assessment under different possible scenarios is a source of uncertainty that may lead to concerning financial losses. We address this issue, first, by adapting a robust framework to the class of spectral risk measures. Second, we propose a Deviation-based approach to quantify uncertainty. Furthermore, the theory is illustrated with a practical case study from NASDAQ index.