M. Ángeles Carnero , Ángel León , Trino-Manuel Ñíguez
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This paper introduces new upper bounds for tail risk measures, such as value-at-risk and expected shortfall, based on Bhattacharyya (1987) inequality. These enhanced bounds for losses consider higher-order moments like skewness and kurtosis, which sets them apart from the conventional one-sided Vysochanskii and Petunin (1980) and Cantelli (1928) inequalities. While the simplicity and reliance on estimating only the first two moments can make the latter bounds attractive, the practicality and effectiveness of the new bounds position them as a compelling alternative for risk measurement. We empirically analyze S&P 100 index stocks to illustrate our findings. Our results suggest tighter Basel multipliers and reduced minimum capital requirements.
期刊介绍：
Finance Research Letters welcomes submissions across all areas of finance, aiming for rapid publication of significant new findings. The journal particularly encourages papers that provide insight into the replicability of established results, examine the cross-national applicability of previous findings, challenge existing methodologies, or demonstrate methodological contingencies.
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