openAI-math-dataset / lean /OAI /Probability /FreeIsing /Stochastic /StoppedSimpleIntegral.lean
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import Mathlib
namespace OAI
noncomputable section
open MeasureTheory Filter
open scoped Topology
namespace Problem367.StoppedSimpleIntegral
variable {Ω ι : Type*} [mΩ : MeasurableSpace Ω] [LinearOrder ι]
{P : Measure Ω} [IsFiniteMeasure P] {F : Filtration ι mΩ}
{B : ι → Ω → ℝ}
theorem condExp_eval_eq_min (hB : Martingale B F P) (s t : ι) :
P[B t | F s] =ᵐ[P] B (min s t) := by
rcases le_total s t with hst | hts
· simpa only [min_eq_left hst] using hB.condExp_ae_eq hst
· rw [min_eq_right hts]
exact (condExp_of_stronglyMeasurable (F.le s)
((hB.stronglyMeasurable t).mono (F.mono hts)) (hB.integrable t)).eventuallyEq
def intervalSum (B : ι → Ω → ℝ) (H : Ω → ℝ) (a b t : ι) (ω : Ω) : ℝ :=
H ω * (B (min t b) ω - B (min t a) ω)
omit [IsFiniteMeasure P] in
theorem intervalSum_stronglyAdapted
(hB : Martingale B F P) {a b : ι} (hab : a ≤ b)
{H : Ω → ℝ} (hH : StronglyMeasurable[F a] H) :
StronglyAdapted F (intervalSum B H a b) := by
intro t
rcases le_total t a with hta | hat
· have heq : intervalSum B H a b t = 0 := by
funext ω
simp only [intervalSum, min_eq_left hta, min_eq_left (hta.trans hab),
sub_self, mul_zero, Pi.zero_apply]
rw [heq]
exact stronglyMeasurable_zero
· exact ((hH.mono (F.mono hat)).mul
(((hB.stronglyMeasurable (min t b)).mono (F.mono (min_le_left _ _))).sub
((hB.stronglyMeasurable (min t a)).mono (F.mono (min_le_left _ _)))))
theorem intervalSum_eq_condExp_terminal
(hB : Martingale B F P) {a b : ι} (hab : a ≤ b)
{H : Ω → ℝ} (hH : StronglyMeasurable[F a] H) {K : ℝ}
(hbound : ∀ᵐ ω ∂P, ‖H ω‖ ≤ K) (t : ι) :
P[(fun ω => H ω * (B b ω - B a ω)) | F t] =ᵐ[P]
intervalSum B H a b t := by
have hDint : Integrable (fun ω => B b ω - B a ω) P :=
(hB.integrable b).sub (hB.integrable a)
have hYint : Integrable (fun ω => H ω * (B b ω - B a ω)) P :=
hDint.bdd_mul (hH.mono (F.le a)).aestronglyMeasurable hbound
rcases le_total t a with hta | hat
· have hzero : P[(fun ω => B b ω - B a ω) | F a] =ᵐ[P] fun _ => 0 := by
have hs := condExp_sub (hB.integrable b) (hB.integrable a) (F a)
filter_upwards [hs, hB.condExp_ae_eq hab, hB.condExp_ae_eq (le_refl a)]
with ω hs hb ha
change P[(fun ω => B b ω - B a ω) | F a] ω =
P[B b | F a] ω - P[B a | F a] ω at hs
simpa only [hb, ha, sub_self] using hs
have hyzero : P[(fun ω => H ω * (B b ω - B a ω)) | F a] =ᵐ[P] fun _ => 0 := by
have hp := condExp_mul_of_stronglyMeasurable_left hH hYint hDint
filter_upwards [hp, hzero] with ω hp hz
change P[(fun ω => H ω * (B b ω - B a ω)) | F a] ω =
H ω * P[(fun ω => B b ω - B a ω) | F a] ω at hp
simpa only [hz, mul_zero] using hp
have htower := condExp_condExp_of_le (μ := P) (F.mono hta) (F.le a)
(f := fun ω => H ω * (B b ω - B a ω))
calc
P[(fun ω => H ω * (B b ω - B a ω)) | F t] =ᵐ[P]
P[P[(fun ω => H ω * (B b ω - B a ω)) | F a] | F t] := htower.symm
_ =ᵐ[P] P[(fun _ : Ω => (0 : ℝ)) | F t] := condExp_congr_ae hyzero
_ =ᵐ[P] intervalSum B H a b t := by
change P[(0 : Ω → ℝ) | F t] =ᵐ[P] intervalSum B H a b t
rw [condExp_zero]
apply Filter.Eventually.of_forall
intro ω
simp only [intervalSum, min_eq_left hta, min_eq_left (hta.trans hab),
Pi.zero_apply, sub_self, mul_zero]
· have hp := condExp_mul_of_stronglyMeasurable_left (hH.mono (F.mono hat)) hYint hDint
have hs := condExp_sub (hB.integrable b) (hB.integrable a) (F t)
filter_upwards [hp, hs, condExp_eval_eq_min hB t b, condExp_eval_eq_min hB t a]
with ω hp hs hb ha
change P[(fun ω => H ω * (B b ω - B a ω)) | F t] ω =
H ω * P[(fun ω => B b ω - B a ω) | F t] ω at hp
change P[(fun ω => B b ω - B a ω) | F t] ω =
P[B b | F t] ω - P[B a | F t] ω at hs
rw [hp, hs, hb, ha]
rfl
theorem intervalSum_martingale
(hB : Martingale B F P) {a b : ι} (hab : a ≤ b)
{H : Ω → ℝ} (hH : StronglyMeasurable[F a] H) {K : ℝ}
(hbound : ∀ᵐ ω ∂P, ‖H ω‖ ≤ K) :
Martingale (intervalSum B H a b) F P :=
(martingale_condExp (fun ω => H ω * (B b ω - B a ω)) F P).congr
(intervalSum_stronglyAdapted hB hab hH)
(intervalSum_eq_condExp_terminal hB hab hH hbound)
theorem finite_intervalSum_martingale {J : Type*}
(hB : Martingale B F P) (s : Finset J) (a b : J → ι) (H : J → Ω → ℝ)
(hab : ∀ i ∈ s, a i ≤ b i)
(hH : ∀ i ∈ s, StronglyMeasurable[F (a i)] (H i))
(K : J → ℝ) (hbound : ∀ i ∈ s, ∀ᵐ ω ∂P, ‖H i ω‖ ≤ K i) :
Martingale (fun t ω => ∑ i ∈ s, intervalSum B (H i) (a i) (b i) t ω) F P := by
classical
induction s using Finset.induction_on with
| empty =>
convert martingale_zero ℝ F P using 1
ext t ω
simp
| @insert i s his ih =>
have hi := intervalSum_martingale hB (hab i (Finset.mem_insert_self i s))
(hH i (Finset.mem_insert_self i s)) (hbound i (Finset.mem_insert_self i s))
have hs := ih (fun j hj => hab j (Finset.mem_insert_of_mem hj))
(fun j hj => hH j (Finset.mem_insert_of_mem hj))
(fun j hj => hbound j (Finset.mem_insert_of_mem hj))
convert hi.add hs using 1
ext t ω
simp only [Finset.sum_insert his, Pi.add_apply]
theorem martingale_of_pointwise_time_L1_limit
{N : Type*} {l : Filter N} [l.NeBot]
{X : N → ι → Ω → ℝ} {Y : ι → Ω → ℝ}
(hX : ∀ n, Martingale (X n) F P)
(hY : StronglyAdapted F Y) (hYint : ∀ t, Integrable (Y t) P)
(hlim : ∀ t, Tendsto (fun n => eLpNorm (X n t - Y t) 1 P) l (𝓝 0)) :
Martingale Y F P := by
refine ⟨hY, ?_⟩
intro s t hst
apply (ae_eq_condExp_of_forall_setIntegral_eq (F.le s) (hYint t)
(fun A hA _ => (hYint s).integrableOn) ?_ (hY s).aestronglyMeasurable).symm
intro A hA hAfin
have hs := tendsto_setIntegral_of_L1' (Y s)
(Filter.Eventually.of_forall (fun n => (hX n).integrable s)) (hlim s) A
have ht := tendsto_setIntegral_of_L1' (Y t)
(Filter.Eventually.of_forall (fun n => (hX n).integrable t)) (hlim t) A
have heq : (fun n => ∫ ω in A, X n s ω ∂P) = (fun n => ∫ ω in A, X n t ω ∂P) :=
funext (fun n => (hX n).setIntegral_eq hst hA)
rw [heq] at hs
exact tendsto_nhds_unique hs ht
end Problem367.StoppedSimpleIntegral
end
end OAI