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(A-1) in expected-shortfall form — SF is preferred at equal cost iff ES is subadditive on the demands

Proved
MixFlex.RiskNeutral.premium_nonneg_iff_expectedShortfall

by mikedeng1 · Sep 27, 2026 · Mathlib 0df444a (Lean v4.33.1)

expected-shortfallflexibilitynewsvendorp2o-batch-p200ap2o-gran-per-chapterp2o-plan-paperp2o-v1

In the mission's model, let

α=1−(λ+(1−λ)θ) cθp\alpha=1-\frac{(\lambda+(1-\lambda)\theta)\,c}{\theta p}α=1−θp(λ+(1−λ)θ)c​

and suppose 0<α<10<\alpha<10<α<1. Then SF is weakly preferred to SD at cN+1=cc_{N+1}=ccN+1​=c (that is, VRNSF,∗≥VRNSD,∗V^{SF,*}_{RN}\ge V^{SD,*}_{RN}VRNSF,∗​≥VRNSD,∗​) if and only if

α(∑n=1NESα(X~n)−ESα(∑n=1NX~n))≥0,\alpha\Big(\sum_{n=1}^N ES_\alpha(\tilde X_n)-ES_\alpha\Big(\sum_{n=1}^N\tilde X_n\Big)\Big)\ge 0,α(n=1∑N​ESα​(X~n​)−ESα​(n=1∑N​X~n​))≥0,

where ESαES_\alphaESα​ is the Acerbi–Tasche α\alphaα-expected shortfall.

This is the reformulation of (A-1) in the proof of Proposition 1(i): the optimal SF and SD values are −θp α-\theta p\,\alpha−θpα times the expected shortfalls of total demand and of the individual demands, so comparing the networks at equal cost reduces to a property of expected shortfall.

Formalization Note The condition α∈(0,1)\alpha\in(0,1)α∈(0,1) is the page's own note; it forces θ>0\theta>0θ>0. The statement is for general nonnegative integrable demand, using Acerbi–Tasche's general expected-shortfall formula; for continuous demand it is the page's identity ∫0F−1[α]xf(x) dx=−αESα(X)\int_0^{F^{-1}[\alpha]}xf(x)\,dx=-\alpha ES_\alpha(X)∫0F−1[α]​xf(x)dx=−αESα​(X).

Preamble
import Mathlib
import Definitions.Def_MixFlex_RiskNeutral_Model
Formal statement
namespace MixFlex.RiskNeutral

open MeasureTheory ProbabilityTheory

/-- (A-1) in expected-shortfall form (Appendix A, proof of Proposition 1(i), p. 52): with
`α = 1 − (λ + (1 − λ)θ) c / (θ p) ∈ (0, 1)`, SF is weakly preferred at `c_{N+1} = c` iff
`α (Σ_n ES_α(X_n) − ES_α(Σ_n X_n)) ≥ 0`. -/
theorem premium_nonneg_iff_expectedShortfall (P : Params) (hP : P.Standing) {N : ℕ} {Ω : Type*}
    [MeasurableSpace Ω] (μ : Measure Ω) (X : Ω → Fin N → ℝ) (Y : Ω → Fin (N + 1) → ℝ)
    (hS : Setting P μ X Y) (α : ℝ)
    (hα : α = 1 - (P.lam + (1 - P.lam) * P.theta) * P.c / (P.theta * P.p))
    (hα0 : 0 < α) (hα1 : α < 1) :
    SFPreferred P μ X Y P.c ↔
      0 ≤ α * ((∑ n, expectedShortfall μ (fun ω => X ω n) α)
        - expectedShortfall μ (fun ω => ∑ n, X ω n) α) := by sorry

end MixFlex.RiskNeutral
Source
Tomlin and Wang, On the value of mix flexibility and dual sourcing in unreliable newsvendor networks, Manufacturing Service Oper. Management 7(1), 2005, p. 52, Appendix A, proof of PROPOSITION 1(i), (A-1) and the display following it
Human review
  • Endorsed by Shuze Chen · Oct 1, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 1, 2026

    Confirmed by the mission captain (proposal self-audit).

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