The Price of Safety: Convexity, Expected Shortfall, and the Economics of Protection

AbstractWhat does an option premium pay for, and what is sacrificed to reduce tail risk? This paper joins those questions through convexity. The cost of a payoff, net of its affine component, is its curvature integrated against the out-of-the-money option surface. On the risk side, the Cost of Managing Risk is expected return sacrificed per unit of expected-shortfall reduction and decomposes into financed premium expenditure, unconditional expected payout, and tail-conditional indemnity.The bridge is the Rockafellar–Uryasev representation. Expected shortfall is a physicalmeasure expectation of a put payoff at the Value-at-Risk strike, whereas the market quotes its risk-neutral value. Their difference is the payoff’s pricing-kernel covariance. A spectral risk measure extends this result through a positive Kusuoka mixture of physical puts; atoms in the mixture become atoms at the corresponding quantile strikes. Consequently, the marginal cost of a financed put hedge is, to first order, a normalised option-insurance premium plus the opportunity cost of premium capital. In the benchmark, the capital term is small. This makes protection costs auditable against the option surface: the revised estimates examined here imply roughly five-and-a-half-volatility-point markups under the stated lognormal diagnostic.The framework yields three allocation results. First, under a linear premium budget and locally fixed tail, the hedge minimizing expected shortfall concentrates protection at the strike maximising tail indemnity per financed premium unit. Second, after affine exposure is fixed, an expected-shortfall constraint assigns direct local value only to curvature below the Value-at-Risk strike; right-wing curvature has no direct first-order indemnity value.Third, buying and dynamically manufacturing protection compare an option wedge with realised-variance and tracking costs. This gives measurable conditions under which dynamic overlays can outperform purchased options while leaving the ranking sample-, model-, and implementation-dependent. The paper thereby connects coherent risk

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-26
DOI
https://doi.org/10.5281/zenodo.21604532
Primary Topic
Stochastic processes and financial applications
Type
preprint
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The Price of Safety: Convexity, Expected Shortfall, and the Economics of Protection

Miquel Noguer Alonso
Zenodo (CERN European Organization for Nuclear Research)
Stochastic processes and financial applications
preprint

The Price of Safety: Convexity, Expected Shortfall, and the Economics of Protection

Miquel Noguer Alonso
preprint en

Abstract

AbstractWhat does an option premium pay for, and what is sacrificed to reduce tail risk? This paper joins those questions through convexity. The cost of a payoff, net of its affine component, is its curvature integrated against the out-of-the-money option surface. On the risk side, the Cost of Managing Risk is expected return sacrificed per unit of expected-shortfall reduction and decomposes into financed premium expenditure, unconditional expected payout, and tail-conditional indemnity.The bridge is the Rockafellar–Uryasev representation. Expected shortfall is a physicalmeasure expectation of a put payoff at the Value-at-Risk strike, whereas the market quotes its risk-neutral value. Their difference is the payoff’s pricing-kernel covariance. A spectral risk measure extends this result through a positive Kusuoka mixture of physical puts; atoms in the mixture become atoms at the corresponding quantile strikes. Consequently, the marginal cost of a financed put hedge is, to first order, a normalised option-insurance premium plus the opportunity cost of premium capital. In the benchmark, the capital term is small. This makes protection costs auditable against the option surface: the revised estimates examined here imply roughly five-and-a-half-volatility-point markups under the stated lognormal diagnostic.The framework yields three allocation results. First, under a linear premium budget and locally fixed tail, the hedge minimizing expected shortfall concentrates protection at the strike maximising tail indemnity per financed premium unit. Second, after affine exposure is fixed, an expected-shortfall constraint assigns direct local value only to curvature below the Value-at-Risk strike; right-wing curvature has no direct first-order indemnity value.Third, buying and dynamically manufacturing protection compare an option wedge with realised-variance and tracking costs. This gives measurable conditions under which dynamic overlays can outperform purchased options while leaving the ranking sample-, model-, and implementation-dependent. The paper thereby connects coherent risk

Zenodo (CERN European Organization for Nuclear Research)
Stochastic processes and financial applications
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