Zero-barrier reflected value from positive-barrier scale identities and finite right derivative
ProvedAvramDividend.Classical.barrierStrategy_zero_boundary_of_positive_ratio_and_finite_deriv_limitavram-dividendfinite-derivativeroot-prerequisitestochastic-reflectionzero-cap
If the actual positive reflected barrier rewards equal W(a)/W'(a) at reciprocal barriers, and the scale function is continuous at zero with an ordinary positive-side derivative tending to a nonzero finite d, the zero-barrier stopped dividend value equals the exact scale-function boundary expression. This combines proved stochastic monotone convergence, derivative EReal conversion, and real quotient convergence.
Preamble
import Mathlib.Analysis.SpecificLimits.Basic import Mathlib.Topology.ContinuousOn import Mathlib.Tactic.Positivity import Theorems.Thm_AvramDividend_Classical_barrierStrategy_zero_boundary_of_positive_scale_limit import Theorems.Thm_AvramDividend_Classical_scale_ratio_reciprocal_tendsto_of_deriv_limit import Theorems.Thm_AvramDividend_Classical_barrierValue_zero_eq_ratio_of_finite_derivZeroPlus import Theorems.Thm_AvramDividend_Classical_derivZeroPlus_eq_coe_of_right_tendsto open AvramDividend.Classical MeasureTheory Filter Set open scoped NNReal ENNReal
Formal statement
theorem AvramDividend.Classical.barrierStrategy_zero_boundary_of_positive_ratio_and_finite_deriv_limit
{Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
{𝓕 : Filtration ℝ≥0 mΩ}
(X : SpectrallyNegativeLevy P 𝓕) (q : ℝ) (W : ℝ → ℝ)
(hscale : ∀ n : ℕ,
barrierSupValue X (1 / ((n : ℝ) + 1)) q =
ENNReal.ofReal (W (1 / ((n : ℝ) + 1)) /
deriv W (1 / ((n : ℝ) + 1))))
(hcont : ContinuousWithinAt W (Ici (0 : ℝ)) 0)
(d : ℝ) (hd : d ≠ 0)
(hderiv : Tendsto (fun y : ℝ => deriv W y)
(nhdsWithin (0 : ℝ) (Ioi 0)) (nhds d)) :
dividendValue X q 0 (barrierStrategy X 0 0) =
ENNReal.ofReal (barrierValue W 0 0) := by sorrySource
Pinned Mathlib one-sided topology; canonical accepted Avram scale-ratio, zero-barrier stochastic convergence, derivative-liminf and boundary ratio lemmas.