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import OAI.Probability.FreeIsing.Brownian.FiltrationIntegralProperties
import OAI.Probability.FreeIsing.Stochastic.StoppedBrownianIntegral
namespace OAI
noncomputable section
open MeasureTheory ProbabilityTheory Filter
open scoped NNReal Topology
namespace Problem367.BrownianIntegralProcess
variable {Ω : Type*} [mΩ : MeasurableSpace Ω] {P : Measure Ω}
theorem meanSquare_condExp_sub_le [IsFiniteMeasure P]
(m : MeasurableSpace Ω) {X Y : Ω → ℝ}
(hX : MemLp X 2 P) (hY : MemLp Y 2 P) :
(∫ ω, (P[X | m] ω - P[Y | m] ω) ^ 2 ∂P) ≤
∫ ω, (X ω - Y ω) ^ 2 ∂P := by
have hsub := condExp_sub (hX.integrable (by norm_num))
(hY.integrable (by norm_num)) m
calc
_ = ∫ ω, (P[X - Y | m] ω) ^ 2 ∂P := by
apply integral_congr_ae
filter_upwards [hsub] with ω hω
change P[X - Y | m] ω = P[X | m] ω - P[Y | m] ω at hω
rw [hω]
_ ≤ _ := by
have hbound := integral_norm_condExp_rpow_le (m := m)
(by norm_num : (1 : ℝ) ≤ 2)
(f := X - Y) (by
simpa only [Real.rpow_two, Real.norm_eq_abs, sq_abs, Pi.sub_apply] using
(hX.sub hY).integrable_sq)
simpa only [Real.rpow_two, Real.norm_eq_abs, sq_abs, Pi.sub_apply] using hbound
theorem finite_stoppedSum_eq_condExp [IsFiniteMeasure P]
{F : Filtration ℝ≥0 mΩ} {B : ℝ≥0 → Ω → ℝ}
(hB : Martingale B F P) (s : Finset ℕ) (a b : ℕ → ℝ≥0)
(H : ℕ → Ω → ℝ) (hab : ∀ i ∈ s, a i ≤ b i)
(hH : ∀ i ∈ s, StronglyMeasurable[F (a i)] (H i))
(C : ℕ → ℝ) (hb : ∀ i ∈ s, ∀ᵐ ω ∂P, ‖H i ω‖ ≤ C i) (t : ℝ≥0) :
P[(fun ω => ∑ i ∈ s, H i ω * (B (b i) ω - B (a i) ω)) | F t] =ᵐ[P]
fun ω => ∑ i ∈ s, StoppedSimpleIntegral.intervalSum B (H i) (a i) (b i) t ω := by
have hint (i : ℕ) (hi : i ∈ s) :
Integrable (fun ω => H i ω * (B (b i) ω - B (a i) ω)) P :=
((hB.integrable (b i)).sub (hB.integrable (a i))).bdd_mul
((hH i hi).mono (F.le (a i))).aestronglyMeasurable (hb i hi)
have hsum := condExp_finsetSum hint (F t)
have hsumFun : (∑ i ∈ s, fun ω => H i ω * (B (b i) ω - B (a i) ω)) =
(fun ω => ∑ i ∈ s, H i ω * (B (b i) ω - B (a i) ω)) := by
funext ω
simp only [Finset.sum_apply]
rw [hsumFun] at hsum
have heach : ∀ᵐ ω ∂P, ∀ i ∈ s,
P[(fun ω => H i ω * (B (b i) ω - B (a i) ω)) | F t] ω =
StoppedSimpleIntegral.intervalSum B (H i) (a i) (b i) t ω :=
s.eventually_all.mpr (fun i hi =>
StoppedSimpleIntegral.intervalSum_eq_condExp_terminal hB (hab i hi) (hH i hi) (hb i hi) t)
filter_upwards [hsum, heach] with ω hsum heach
simp only [Finset.sum_apply] at hsum
rw [hsum]
exact Finset.sum_congr rfl (fun i hi => heach i hi)
def stoppedUniformSum (B H : ℝ≥0 → Ω → ℝ) (T : ℝ≥0) (n : ℕ)
(t : ℝ≥0) (ω : Ω) : ℝ :=
∑ i ∈ Finset.range n, StoppedSimpleIntegral.intervalSum B
(H (BrownianGrid.uniformGrid T n i)) (BrownianGrid.uniformGrid T n i)
(BrownianGrid.uniformGrid T n (i + 1)) t ω
theorem stoppedUniformSum_eq_condExp
{B H : ℝ≥0 → Ω → ℝ} {F : Filtration ℝ≥0 mΩ}
(hB : IsPreBrownianReal B P) (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P)
(hH : StronglyAdapted F H) {C : ℝ}
(hb : ∀ᵐ ω ∂P, ∀ t, |H t ω| ≤ C) (T : ℝ≥0) (n : ℕ) (t : ℝ≥0) :
P[BrownianGrid.uniformSum B H T n | F t] =ᵐ[P] stoppedUniformSum B H T n t := by
let : IsProbabilityMeasure P := hB.isGaussianProcess.isProbabilityMeasure
apply finite_stoppedSum_eq_condExp (BrownianFiltration.martingale_of_independent_past hB hAd hind)
(Finset.range n) (BrownianGrid.uniformGrid T n)
(fun i => BrownianGrid.uniformGrid T n (i + 1))
(fun i => H (BrownianGrid.uniformGrid T n i))
(fun i _ => BrownianGrid.uniformGrid_mono T n (Nat.le_succ i))
(fun i _ => hH _) (fun _ => C)
intro i hi
filter_upwards [hb] with ω hω
simpa only [Real.norm_eq_abs] using hω (BrownianGrid.uniformGrid T n i)
theorem exists_stopped_uniform_integral_process
{B H : ℝ≥0 → Ω → ℝ} {F : Filtration ℝ≥0 mΩ}
(hB : IsPreBrownianReal B P) (hAd : StronglyAdapted F B)
(hind : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω => B t ω - B s ω) inferInstance) (F s) P)
(hH : StronglyAdapted F H)
(hc : ∀ᵐ ω ∂P, Continuous (fun t => H t ω))
{C : ℝ} (hC : 0 ≤ C) (hb : ∀ᵐ ω ∂P, ∀ t, |H t ω| ≤ C) (T : ℝ≥0) :
∃ M : ℝ≥0 → Ω → ℝ, Martingale M F P ∧
(∀ t, MemLp (M t) 2 P) ∧
(∀ t, (∫ ω, M t ω ∂P) = 0) ∧
(∀ t, T ≤ t → M t = M T) ∧
(∫ ω, (M T ω) ^ 2 ∂P) =
(∫ t in (0 : ℝ)..(T : ℝ), ∫ ω, (H t.toNNReal ω) ^ 2 ∂P) ∧
(∀ t, Tendsto (fun n => ∫ ω,
(stoppedUniformSum B H T n t ω - M t ω) ^ 2 ∂P) atTop (𝓝 0)) := by
let : IsProbabilityMeasure P := hB.isGaussianProcess.isProbabilityMeasure
obtain ⟨I, hIm, hI2, hIzero, hIiso, hIlim⟩ :=
BrownianFiltrationGrid.exists_terminal_uniform_integral_isometry
hB hAd hind H hH hc hC hb T
let M : ℝ≥0 → Ω → ℝ := fun t => P[I | F t]
have hIint : Integrable I P := hI2.integrable (by norm_num)
have hafter (t : ℝ≥0) (ht : T ≤ t) : M t = I :=
condExp_of_stronglyMeasurable (F.le t) (hIm.mono (F.mono ht)) hIint
have hH2 (t : ℝ≥0) : MemLp (H t) 2 P := by
apply MemLp.of_bound ((hH t).mono (F.le t)).aestronglyMeasurable C
filter_upwards [hb] with ω hω
simpa only [Real.norm_eq_abs] using hω t
refine ⟨M, martingale_condExp I F P, ?_, ?_, ?_, ?_, ?_⟩
· intro t
exact hI2.condExp (by norm_num)
· intro t
exact (integral_condExp (F.le t)).trans hIzero
· intro t ht
exact (hafter t ht).trans (hafter T le_rfl).symm
· rw [hafter T le_rfl]
exact hIiso
· intro t
apply squeeze_zero (fun n => integral_nonneg (fun ω => sq_nonneg _)) ?_ hIlim
intro n
calc
_ = ∫ ω, (P[BrownianGrid.uniformSum B H T n | F t] ω - P[I | F t] ω) ^ 2 ∂P := by
apply integral_congr_ae
filter_upwards [stoppedUniformSum_eq_condExp hB hAd hind hH hb T n t] with ω hω
change (stoppedUniformSum B H T n t ω - P[I | F t] ω) ^ 2 = _
rw [hω]
_ ≤ _ := meanSquare_condExp_sub_le (F t)
(BrownianFiltrationGrid.uniformSum_memLp hB hAd hind H hH hH2 T n) hI2
end Problem367.BrownianIntegralProcess
end
end OAI