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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/1812.06185 |
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Table of Contents:
- Systemic risk measures are crucial for the stability of financial markets, yet classical formulations fail to capture the complexity of market volatility. We propose a new framework for systemic risk measurement on the variable-exponent Bochner-Lebesgue space $L^{p(\cdot)}$, where the exponent $p(\cdot)$ is a random variable rather than a deterministic constant parameter, thereby inherently encoding latent market volatility. By constructing suitable deterministic auxiliary functions and single-firm risk measures, we decompose the quantification of systemic risk in $L^{p(\cdot)}$ into two sequential steps, ultimately deriving its dual representations. Several examples are provided to illustrate the theoretical results.