Itô integral
StructureElementary integrand#✓fully proved
An elementary integrand for a filtration F indexed by ℝ≥0: partition times
time 0 ≤ ⋯ ≤ time n and coefficients coeff i, bounded by bound and measurable with respect
to F (time i), representing the process ∑ i, coeff i 1_{(time i, time (i + 1)]}. Equal
consecutive times are allowed (the corresponding interval is empty).
ProbabilityTheory.ElementaryIntegrand · 15 lines
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
bound : ℝ
/-- The coefficients are bounded by `bound`. -/
abs_coeff_le : ∀ i ω, |coeff i ω| ≤ bound
n : ℕ
MathlibExt/Probability/ElementaryItoIntegral.lean:76
time : Fin (n + 1) → ℝ≥0
MathlibExt/Probability/ElementaryItoIntegral.lean:78
coeff : Fin n → Ω → ℝ
MathlibExt/Probability/ElementaryItoIntegral.lean:82
bound : ℝ
MathlibExt/Probability/ElementaryItoIntegral.lean:86
Used by 40
TheoremSecond moment of a Brownian increment#✓fully proved
The second moment of a Brownian increment: E[(B v - B r)²] = v - r for r ≤ v.
theorem IsPreBrownianReal.integral_sub_sq {P : Measure Ω} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P) {r v : ℝ≥0} (hrv : r ≤ v) :
P[fun ω ↦ (B v ω - B r ω) ^ 2] = (v : ℝ) - r
Used by 2
DefinitionElementary integrand as a process#✓fully proved
The elementary integrand as a process: u ↦ ∑ i, coeff i 1_{(time i, time (i + 1)]}(u).
noncomputable def toProcess (H : ElementaryIntegrand F) (u : ℝ≥0) (ω : Ω) : ℝ :=
∑ i, (Set.Ioc (H.time i.castSucc) (H.time i.succ)).indicator (fun _ ↦ H.coeff i ω) u
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 1 · Used by 28
DefinitionItô integral of an elementary integrand#✓fully proved
The Itô integral of an elementary integrand against a process B:
t ↦ ∑ i, coeff i (B (time (i + 1) ∧ t) - B (time i ∧ t)).
def itoIntegral (H : ElementaryIntegrand F) (B : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) (ω : Ω) : ℝ :=
∑ i, H.coeff i ω * (B (min (H.time i.succ) t) ω - B (min (H.time i.castSucc) t) ω)
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 1 · Used by 26
C¹ integrand · The Itô integral is well defined · Itô's formula · Itô integral of the left-point integrand is the left-point sum · The pathwise Langevin solution driven by Brownian motion is Gaussian · Elementary Itô integrals agree for modificationsDefinitionSingle-step elementary integrand#✓fully proved
The elementary integrand ξ 1_{(a, b]} for a ≤ b and an F a-measurable ξ bounded by
C.
def single (a b : ℝ≥0) (hab : a ≤ b) (ξ : Ω → ℝ) (hξ : Measurable[F a] ξ) (C : ℝ)
(hξC : ∀ ω, |ξ ω| ≤ C) : ElementaryIntegrand F where
n := 1
time := ![a, b]
monotone_time := by
refine Fin.monotone_iff_le_succ.mpr fun i ↦ ?_
fin_cases i
simpa using hab
coeff := fun _ ↦ ξ
measurable_coeff := fun i ↦ by obtain rfl : i = 0 := Subsingleton.elim _ _; exact hξ
bound := C
abs_coeff_le := fun _ ↦ hξC
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 1 · Used by 3
TheoremProcess of a single-step elementary integrand#✓fully proved
The process of single a b hab ξ hξ C hξC is u ↦ ξ 1_{(a, b]}(u).
theorem toProcess_single (a b : ℝ≥0) (hab : a ≤ b) (ξ : Ω → ℝ) (hξ : Measurable[F a] ξ)
(C : ℝ) (hξC : ∀ ω, |ξ ω| ≤ C) :
(single a b hab ξ hξ C hξC).toProcess =
fun u ω ↦ (Set.Ioc a b).indicator (fun _ ↦ ξ ω) u
def single (a b : ℝ≥0) (hab : a ≤ b) (ξ : Ω → ℝ) (hξ : Measurable[F a] ξ) (C : ℝ)
(hξC : ∀ ω, |ξ ω| ≤ C) : ElementaryIntegrand F where
n := 1
time := ![a, b]
monotone_time := by
refine Fin.monotone_iff_le_succ.mpr fun i ↦ ?_
fin_cases i
simpa using hab
coeff := fun _ ↦ ξ
measurable_coeff := fun i ↦ by obtain rfl : i = 0 := Subsingleton.elim _ _; exact hξ
bound := C
abs_coeff_le := fun _ ↦ hξC
MathlibExt/Probability/ElementaryItoIntegral.lean:164
Uses 3 · Used by 1
TheoremElementary integrands#✓fully proved
The Itô integral of ξ 1_{(a, b]} is
ξ (B (b ∧ t) - B (a ∧ t)) (Karatzas–Shreve 1991, Section 3.2.A); this holds for every
process B and every ω, by definition.
theorem itoIntegral_single (a b : ℝ≥0) (hab : a ≤ b) (ξ : Ω → ℝ) (hξ : Measurable[F a] ξ)
(C : ℝ) (hξC : ∀ ω, |ξ ω| ≤ C) (B : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) (ω : Ω) :
(single a b hab ξ hξ C hξC).itoIntegral B t ω =
ξ ω * (B (min b t) ω - B (min a t) ω)
def single (a b : ℝ≥0) (hab : a ≤ b) (ξ : Ω → ℝ) (hξ : Measurable[F a] ξ) (C : ℝ)
(hξC : ∀ ω, |ξ ω| ≤ C) : ElementaryIntegrand F where
n := 1
time := ![a, b]
monotone_time := by
refine Fin.monotone_iff_le_succ.mpr fun i ↦ ?_
fin_cases i
simpa using hab
coeff := fun _ ↦ ξ
measurable_coeff := fun i ↦ by obtain rfl : i = 0 := Subsingleton.elim _ _; exact hξ
bound := C
abs_coeff_le := fun _ ↦ hξC
MathlibExt/Probability/ElementaryItoIntegral.lean:164
Uses 3 · Used by 1
TheoremElementary Itô integral vanishes at time zero#✓fully proved
The elementary Itô integral vanishes at time 0.
@[simp]
theorem itoIntegral_zero (H : ElementaryIntegrand F) (B : ℝ≥0 → Ω → ℝ) :
H.itoIntegral B 0 = 0
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 2
TheoremItô isometry, discrete form#✓fully proved
For a pre-Brownian motion B adapted to F whose
increments B t - B s are independent of F s,
E[(∫_0^t H dB)²] = ∑ i, E[ξ_i²] (t_{i+1} ∧ t - t_i ∧ t).
theorem integral_itoIntegral_sq_eq_sum (H : ElementaryIntegrand F) {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) (t : ℝ≥0) :
P[fun ω ↦ H.itoIntegral B t ω ^ 2] =
∑ i, P[fun ω ↦ H.coeff i ω ^ 2] *
((min (H.time i.succ) t : ℝ) - (min (H.time i.castSucc) t : ℝ))
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 3 · Used by 1
TheoremPartition intervals of an elementary integrand are disjoint#✓fully proved
The partition intervals of an elementary integrand are pairwise disjoint.
theorem disjoint_Ioc_time
(H : ElementaryIntegrand F) {i j : Fin H.n} (hij : i ≠ j) :
Disjoint (Set.Ioc (H.time i.castSucc) (H.time i.succ))
(Set.Ioc (H.time j.castSucc) (H.time j.succ))
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 1 · Used by 2
TheoremElementary integrand on a partition interval#✓fully proved
On its i-th interval, an elementary integrand equals its i-th coefficient.
theorem toProcess_eq_of_mem (H : ElementaryIntegrand F) {i : Fin H.n} {u : ℝ≥0}
(hu : u ∈ Set.Ioc (H.time i.castSucc) (H.time i.succ)) (ω : Ω) :
H.toProcess u ω = H.coeff i ω
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 3 · Used by 2
TheoremTime integral of a squared elementary integrand#✓fully proved
The time integral of the squared elementary integrand, path by path:
∫_0^t H_u² du = ∑ i, ξ_i² (t_{i+1} ∧ t - t_i ∧ t).
theorem integral_toProcess_sq (H : ElementaryIntegrand F) (t : ℝ≥0) (ω : Ω) :
∫ u in (0 : ℝ)..t, H.toProcess (Real.toNNReal u) ω ^ 2 =
∑ i, H.coeff i ω ^ 2 *
((min (H.time i.succ) t : ℝ) - (min (H.time i.castSucc) t : ℝ))
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 3 · Used by 1
TheoremItô isometry#✓fully proved
Itô isometry for elementary integrands: for a pre-Brownian motion B adapted to F
whose increments B t - B s are independent of F s,
E[(∫_0^t H dB)²] = E ∫_0^t H_u² du (Karatzas–Shreve 1991, Section 3.2.A).
theorem integral_itoIntegral_sq (H : ElementaryIntegrand F) {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) (t : ℝ≥0) :
P[fun ω ↦ H.itoIntegral B t ω ^ 2] =
P[fun ω ↦ ∫ u in (0 : ℝ)..t, H.toProcess (Real.toNNReal u) ω ^ 2]
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
TheoremMartingale property#✓fully proved
For a pre-Brownian motion B adapted to F whose increments
B t - B s are independent of F s, the elementary Itô integral t ↦ ∫_0^t H dB is an
F-martingale.
theorem martingale_itoIntegral (H : ElementaryIntegrand F) {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) :
Martingale (H.itoIntegral B) F P
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 2 · Used by 3
TheoremPolarized Itô isometry#✓fully proved
Polarized Itô isometry for elementary integrands: for a pre-Brownian motion B adapted
to F whose increments B t - B s are independent of F s, and two elementary integrands
H, K (with possibly different partitions),
E[(∫_0^t H dB) (∫_0^t K dB)] = E ∫_0^t H_u K_u du.
theorem integral_itoIntegral_mul (H K : ElementaryIntegrand F) {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) (t : ℝ≥0) :
P[fun ω ↦ H.itoIntegral B t ω * K.itoIntegral B t ω] =
P[fun ω ↦ ∫ u in (0 : ℝ)..t, H.toProcess (Real.toNNReal u) ω *
K.toProcess (Real.toNNReal u) ω]
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 4 · Used by 1
TheoremRiemann–Stieltjes integration by parts, uniform partitions#✓fully proved
For a C¹ function g, a
continuous path w and t ≥ 0, the left-point sums
∑_{k < n} g (t k / n) (w (t (k + 1) / n) - w (t k / n)) converge, as n → ∞, to
g t w t - g 0 w 0 - ∫_0^t g' w.
theorem tendsto_sum_mul_sub_uniform {g : ℝ → ℝ} (hg : ContDiff ℝ 1 g) {w : ℝ → ℝ}
(hw : Continuous w) {t : ℝ} (ht : 0 ≤ t) :
Tendsto (fun n : ℕ ↦ ∑ k ∈ Finset.range n,
g (t * k / n) * (w (t * (k + 1) / n) - w (t * k / n))) atTop
(𝓝 (g t * w t - g 0 * w 0 - ∫ u in (0 : ℝ)..t, deriv g u * w u))
Used by 1
DefinitionLeft-point step approximation of a deterministic integrand#✓fully proved
The left-point step approximation ∑_{k < n} g (t k / n) 1_{(t k / n, t (k + 1) / n]} of a
deterministic g on the uniform partition of [0, t] into n cells, as an
elementary integrand for any filtration F (deterministic coefficients are measurable for every
σ-algebra).
noncomputable def riemann (F : Filtration ℝ≥0 mΩ) (g : ℝ → ℝ) (t : ℝ≥0) (n : ℕ) :
ElementaryIntegrand F where
n := n
time := fun k ↦ t * k / n
monotone_time := fun i j hij ↦ by
have : ((i : ℕ) : ℝ≥0) ≤ (j : ℕ) := by exact_mod_cast hij
dsimp only
gcongr
coeff := fun k _ ↦ g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)
measurable_coeff := fun _ ↦ measurable_const
bound := ∑ k : Fin n, |g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)|
abs_coeff_le := fun k _ ↦
Finset.single_le_sum (f := fun k : Fin n ↦ |g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)|)
(fun _ _ ↦ abs_nonneg _) (Finset.mem_univ k)
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 1 · Used by 7
C¹ integrand · Covariance of the Wiener integrals · The pathwise Langevin solution driven by Brownian motion is GaussianTheoremItô integral of a Riemann step approximation#✓fully proved
The elementary Itô integral of riemann F g t n at time t is the Itô–Riemann sum
∑_{k < n} g (t k / n) (B (t (k + 1) / n) - B (t k / n)).
theorem itoIntegral_riemann (F : Filtration ℝ≥0 mΩ) (g : ℝ → ℝ) (t : ℝ≥0) (n : ℕ)
(B : ℝ≥0 → Ω → ℝ) (ω : Ω) :
(riemann F g t n).itoIntegral B t ω = ∑ k ∈ Finset.range n,
g (t * k / n) *
(B (Real.toNNReal (t * (k + 1) / n)) ω - B (Real.toNNReal (t * k / n)) ω)
noncomputable def riemann (F : Filtration ℝ≥0 mΩ) (g : ℝ → ℝ) (t : ℝ≥0) (n : ℕ) :
ElementaryIntegrand F where
n := n
time := fun k ↦ t * k / n
monotone_time := fun i j hij ↦ by
have : ((i : ℕ) : ℝ≥0) ≤ (j : ℕ) := by exact_mod_cast hij
dsimp only
gcongr
coeff := fun k _ ↦ g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)
measurable_coeff := fun _ ↦ measurable_const
bound := ∑ k : Fin n, |g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)|
abs_coeff_le := fun k _ ↦
⋯
MathlibExt/Probability/ItoRiemannSums.lean:171
TheoremItô–Riemann sums of a deterministic C¹ integrand#✓fully proved
Along every continuous path of B,
the elementary Itô integrals at time t of the left-point approximations of g converge to
Wiener's integration-by-parts expression g t B t - g 0 B 0 - ∫_0^t g'(u) B u du.
theorem tendsto_itoIntegral_riemann (F : Filtration ℝ≥0 mΩ) {g : ℝ → ℝ} (hg : ContDiff ℝ 1 g)
{B : ℝ≥0 → Ω → ℝ} {ω : Ω} (hω : Continuous (B · ω)) (t : ℝ≥0) :
Tendsto (fun n ↦ (riemann F g t n).itoIntegral B t ω) atTop
(𝓝 (g t * B t ω - g 0 * B 0 ω - ∫ u in (0 : ℝ)..t, deriv g u * B u.toNNReal ω))
noncomputable def riemann (F : Filtration ℝ≥0 mΩ) (g : ℝ → ℝ) (t : ℝ≥0) (n : ℕ) :
ElementaryIntegrand F where
n := n
time := fun k ↦ t * k / n
monotone_time := fun i j hij ↦ by
have : ((i : ℕ) : ℝ≥0) ≤ (j : ℕ) := by exact_mod_cast hij
dsimp only
gcongr
coeff := fun k _ ↦ g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)
measurable_coeff := fun _ ↦ measurable_const
bound := ∑ k : Fin n, |g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)|
abs_coeff_le := fun k _ ↦
⋯
MathlibExt/Probability/ItoRiemannSums.lean:171
Uses 4 · Used by 2
TheoremOrnstein–Uhlenbeck path solution by integration by parts#✓fully proved
The pathwise Ornstein–Uhlenbeck solution in integration-by-parts form: with g u = e^{θu},
ouPathSolution θ σ x₀ w t = e^{-θt} x₀ + σ e^{-θt} (g t w t - g 0 w 0 - ∫_0^t g'(u) w u du),
for any path w and any real θ, σ, x₀, t.
theorem ouPathSolution_eq_integration_by_parts (θ σ x₀ : ℝ) (w : ℝ → ℝ) (t : ℝ) :
ouPathSolution θ σ x₀ w t = exp (-θ * t) * x₀ + σ * exp (-θ * t) *
(exp (θ * t) * w t - exp (θ * 0) * w 0 -
∫ u in (0 : ℝ)..t, deriv (fun u ↦ exp (θ * u)) u * w u)
noncomputable def ouPathSolution (θ σ x₀ : ℝ) (w : ℝ → ℝ) (t : ℝ) : ℝ :=
exp (-θ * t) * x₀ +
σ * (w t - exp (-θ * t) * w 0 - θ * ∫ u in (0 : ℝ)..t, exp (-θ * (t - u)) * w u)
MathlibExt/Probability/OrnsteinUhlenbeck.lean:600
Uses 1 · Used by 2
TheoremThe Itô form of the Ornstein–Uhlenbeck solution#✓fully proved
For a Brownian motion B, almost surely,
for every t ≥ 0 and every initial value X₀, the Itô–Riemann sums
e^{-θt} X₀ + σ e^{-θt} ∑_{k < n} e^{θ t k / n} (B (t (k + 1) / n) - B (t k / n)) of
e^{-θt} X₀ + σ ∫_0^t e^{-θ(t-s)} dB_s converge to the pathwise solution ouPathSolution
(any real θ, σ).
theorem IsBrownianReal.ae_tendsto_ou_itoIntegral_riemann {Ω : Type*} {mΩ : MeasurableSpace Ω}
{P : Measure Ω} {B : ℝ≥0 → Ω → ℝ} (hB : IsBrownianReal B P) (F : Filtration ℝ≥0 mΩ)
(θ σ : ℝ) (X₀ : Ω → ℝ) :
∀ᵐ ω ∂P, ∀ t : ℝ≥0, Tendsto (fun n ↦ exp (-θ * t) * X₀ ω + σ * exp (-θ * t) *
(ElementaryIntegrand.riemann F (fun u ↦ exp (θ * u)) t n).itoIntegral B t ω)
atTop (𝓝 (ouPathSolution θ σ (X₀ ω) (fun u ↦ B u.toNNReal ω) t))
noncomputable def riemann (F : Filtration ℝ≥0 mΩ) (g : ℝ → ℝ) (t : ℝ≥0) (n : ℕ) :
ElementaryIntegrand F where
n := n
time := fun k ↦ t * k / n
monotone_time := fun i j hij ↦ by
have : ((i : ℕ) : ℝ≥0) ≤ (j : ℕ) := by exact_mod_cast hij
dsimp only
gcongr
coeff := fun k _ ↦ g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)
measurable_coeff := fun _ ↦ measurable_const
bound := ∑ k : Fin n, |g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)|
abs_coeff_le := fun k _ ↦
⋯
MathlibExt/Probability/ItoRiemannSums.lean:171
noncomputable def ouPathSolution (θ σ x₀ : ℝ) (w : ℝ → ℝ) (t : ℝ) : ℝ :=
exp (-θ * t) * x₀ +
σ * (w t - exp (-θ * t) * w 0 - θ * ∫ u in (0 : ℝ)..t, exp (-θ * (t - u)) * w u)
MathlibExt/Probability/OrnsteinUhlenbeck.lean:600
DefinitionSquared \(L^2\) distance between integrands#✓fully proved
The squared L²(P ⊗ du) distance on (0, t] × Ω between two processes, in ℝ≥0∞:
∫⁻ ω, ∫⁻ u in (0, t], |H u ω - K u ω|² du dP.
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
Used by 26
DefinitionRestriction of a process to the time interval (0, t)#✓fully proved
The process H with its values at times outside (0, t] set to 0. Only the values at
times in (0, t] enter the Itô integral at time t.
noncomputable def restrictIoc (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) (u : ℝ≥0) (ω : Ω) : ℝ :=
(Set.Ioc 0 t).indicator (fun v ↦ H v ω) u
Used by 16
DefinitionItô-approximable process#✓fully proved
A process H is Itô-approximable on [0, t] for the filtration F if it is jointly
measurable on (0, t] × Ω and is the L²(P ⊗ du)-limit on (0, t] × Ω of elementary
integrands. Neither condition involves the values of H at time 0 or after t.
def IsItoApproximable (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
Prop :=
Measurable (fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2) ∧
∃ Hn : ℕ → ElementaryIntegrand F,
Tendsto (fun n ↦ integrandDist P (Hn n).toProcess H t) atTop (𝓝 0)
noncomputable def restrictIoc (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) (u : ℝ≥0) (ω : Ω) : ℝ :=
(Set.Ioc 0 t).indicator (fun v ↦ H v ω) u
MathlibExt/Probability/ItoIntegral.lean:97
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
Uses 4 · Used by 14
DefinitionFunction as an element of \(L^2\)#✓fully proved
A function as an element of L²(P), or 0 if it is not square integrable.
noncomputable def toL2 (P : Measure Ω) (f : Ω → ℝ) : Lp ℝ 2 P :=
if h : MemLp f 2 P then h.toLp f else 0
Used by 13
DefinitionItô integral as an element of \(L^2\)#✓fully proved
The Itô integral ∫_0^t H dB as an element of L²(P): the L² limit of the elementary
Itô integrals of an approximating sequence of elementary integrands when H is Itô-approximable
on [0, t], and 0 otherwise.
noncomputable def itoIntegralL2 (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Lp ℝ 2 P :=
if h : IsItoApproximable P F H t then
limUnder atTop fun n ↦ toL2 P ((h.2.choose n).itoIntegral B t)
else 0
def IsItoApproximable (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
Prop :=
Measurable (fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2) ∧
∃ Hn : ℕ → ElementaryIntegrand F,
Tendsto (fun n ↦ integrandDist P (Hn n).toProcess H t) atTop (𝓝 0)
MathlibExt/Probability/ItoIntegral.lean:103
noncomputable def toL2 (P : Measure Ω) (f : Ω → ℝ) : Lp ℝ 2 P :=
if h : MemLp f 2 P then h.toLp f else 0
MathlibExt/Probability/ItoIntegral.lean:111
Uses 7 · Used by 17
DefinitionItô integral process#✓fully proved
The Itô integral t ↦ ∫_0^t H dB as a real process: an F t-strongly measurable
version of itoIntegralL2 P F B H t when one exists (which is the case under the hypotheses of
the theorems below), and a representative of itoIntegralL2 P F B H t otherwise.
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
noncomputable def itoIntegralL2 (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Lp ℝ 2 P :=
if h : IsItoApproximable P F H t then
limUnder atTop fun n ↦ toL2 P ((h.2.choose n).itoIntegral B t)
else 0
MathlibExt/Probability/ItoIntegral.lean:118
Uses 1 · Used by 19
TheoremItô integral process is a version of the \(L^2\) integral#✓fully proved
The Itô integral process is almost surely equal to itoIntegralL2 at each time.
theorem itoIntegral_ae_eq (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : itoIntegral P F B H t =ᵐ[P] itoIntegralL2 P F B H t
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
noncomputable def itoIntegralL2 (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Lp ℝ 2 P :=
if h : IsItoApproximable P F H t then
limUnder atTop fun n ↦ toL2 P ((h.2.choose n).itoIntegral B t)
else 0
MathlibExt/Probability/ItoIntegral.lean:118
Uses 2 · Used by 10
TheoremRestriction to (0, t) preserves joint measurability#✓fully proved
Restricting a jointly measurable process to the times (0, t] keeps it jointly
measurable.
theorem measurable_restrictIoc {H : ℝ≥0 → Ω → ℝ}
(hH : Measurable fun p : ℝ × Ω ↦ H p.1.toNNReal p.2) (t : ℝ≥0) :
Measurable fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2
noncomputable def restrictIoc (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) (u : ℝ≥0) (ω : Ω) : ℝ :=
(Set.Ioc 0 t).indicator (fun v ↦ H v ω) u
MathlibExt/Probability/ItoIntegral.lean:97
Uses 1 · Used by 12
TheoremIntegrand distance depends only on times in (0, t)#✓fully proved
integrandDist P X Y t only depends on X and Y at times in (0, t].
theorem integrandDist_restrictIoc (P : Measure Ω) (X Y : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
integrandDist P (restrictIoc X t) (restrictIoc Y t) t = integrandDist P X Y t
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
noncomputable def restrictIoc (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) (u : ℝ≥0) (ω : Ω) : ℝ :=
(Set.Ioc 0 t).indicator (fun v ↦ H v ω) u
MathlibExt/Probability/ItoIntegral.lean:97
TheoremLocality of approximability#✓fully proved
Itô-approximability on [0, t] only depends on the
integrand at times in (0, t].
theorem IsItoApproximable.congr {P : Measure Ω} {F : Filtration ℝ≥0 mΩ} {H K : ℝ≥0 → Ω → ℝ}
{t : ℝ≥0} (h : IsItoApproximable P F H t) (hHK : ∀ u ∈ Set.Ioc 0 t, ∀ ω, H u ω = K u ω) :
IsItoApproximable P F K t
def IsItoApproximable (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
Prop :=
Measurable (fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2) ∧
∃ Hn : ℕ → ElementaryIntegrand F,
Tendsto (fun n ↦ integrandDist P (Hn n).toProcess H t) atTop (𝓝 0)
MathlibExt/Probability/ItoIntegral.lean:103
Uses 6 · Used by 1
TheoremElementary integrands are jointly measurable#✓fully proved
An elementary integrand is jointly measurable in (u, ω) (reading u : ℝ through
Real.toNNReal).
theorem measurable_toProcess (H : ElementaryIntegrand F) :
Measurable (fun p : ℝ × Ω ↦ H.toProcess p.1.toNNReal p.2)
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 2 · Used by 9
TheoremUniform bound on an elementary integrand#✓fully proved
An elementary integrand with n intervals is bounded by n * bound.
theorem abs_toProcess_le (H : ElementaryIntegrand F) (u : ℝ≥0) (ω : Ω) :
|H.toProcess u ω| ≤ H.n * H.bound
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 2 · Used by 2
TheoremSquare integrability of the elementary Itô integral#✓fully proved
The elementary Itô integral against a pre-Brownian motion is square integrable.
theorem memLp_itoIntegral (H : ElementaryIntegrand F) {P : Measure Ω} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P) (t : ℝ≥0) :
MemLp (H.itoIntegral B t) 2 P
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 2 · Used by 8
TheoremFinite distance between elementary integrands#✓fully proved
The L²(P ⊗ du) distance between two elementary integrands is finite.
theorem integrandDist_ne_top (H K : ElementaryIntegrand F) {P : Measure Ω} [IsFiniteMeasure P]
(t : ℝ≥0) : integrandDist P H.toProcess K.toProcess t ≠ ⊤
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
Uses 5 · Used by 2
TheoremItô isometry for elementary integrands#✓fully proved
integrandDist of two elementary integrands is the squared L²(P) distance of their Itô
integrals.
theorem integrandDist_eq_dist_sq (H K : ElementaryIntegrand F) {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) (t : ℝ≥0) :
integrandDist P H.toProcess K.toProcess t =
ENNReal.ofReal (dist (toL2 P (H.itoIntegral B t)) (toL2 P (K.itoIntegral B t)) ^ 2)
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
noncomputable def toL2 (P : Measure Ω) (f : Ω → ℝ) : Lp ℝ 2 P :=
if h : MemLp f 2 P then h.toLp f else 0
MathlibExt/Probability/ItoIntegral.lean:111
Uses 10 · Used by 3
TheoremQuasi-triangle inequality for the integrand distance#✓fully proved
Pointwise |x - y|² ≤ 2 |x - z|² + 2 |y - z|², integrated: a quasi-triangle inequality
for integrandDist between jointly measurable processes.
theorem integrandDist_le {P : Measure Ω} {X Y Z : ℝ≥0 → Ω → ℝ}
(hX : Measurable fun p : ℝ × Ω ↦ X p.1.toNNReal p.2)
(hY : Measurable fun p : ℝ × Ω ↦ Y p.1.toNNReal p.2)
(hZ : Measurable fun p : ℝ × Ω ↦ Z p.1.toNNReal p.2) (t : ℝ≥0) :
integrandDist P X Y t ≤ 2 * integrandDist P X Z t + 2 * integrandDist P Y Z t
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
Uses 1 · Used by 4
TheoremThe Itô integral is well defined#✓fully proved
For a pre-Brownian motion B adapted to F with
increments independent of the past, an H jointly measurable on (0, t] × Ω, and any
sequence of elementary integrands Kn converging to H in L²(P ⊗ du) on (0, t] × Ω, the
elementary Itô integrals of Kn converge in L²(P) to itoIntegralL2 P F B H t.
theorem tendsto_toL2_itoIntegral {F : Filtration ℝ≥0 mΩ} {P : Measure Ω} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) {H : ℝ≥0 → Ω → ℝ} {t : ℝ≥0}
(hH : Measurable fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2)
{Kn : ℕ → ElementaryIntegrand F}
(hK : Tendsto (fun n ↦ integrandDist P (Kn n).toProcess H t) atTop (𝓝 0)) :
Tendsto (fun n ↦ toL2 P ((Kn n).itoIntegral B t)) atTop (𝓝 (itoIntegralL2 P F B H t))
noncomputable def restrictIoc (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) (u : ℝ≥0) (ω : Ω) : ℝ :=
(Set.Ioc 0 t).indicator (fun v ↦ H v ω) u
MathlibExt/Probability/ItoIntegral.lean:97
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
noncomputable def toL2 (P : Measure Ω) (f : Ω → ℝ) : Lp ℝ 2 P :=
if h : MemLp f 2 P then h.toLp f else 0
MathlibExt/Probability/ItoIntegral.lean:111
noncomputable def itoIntegralL2 (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Lp ℝ 2 P :=
if h : IsItoApproximable P F H t then
limUnder atTop fun n ↦ toL2 P ((h.2.choose n).itoIntegral B t)
else 0
MathlibExt/Probability/ItoIntegral.lean:118
Uses 13 · Used by 10
TheoremLocality of the Itô integral#✓fully proved
The Itô integral at time t only depends on the integrand
at times in (0, t].
theorem itoIntegralL2_congr {F : Filtration ℝ≥0 mΩ} {P : Measure Ω} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) {H K : ℝ≥0 → Ω → ℝ} {t : ℝ≥0} (hHK : ∀ u ∈ Set.Ioc 0 t, ∀ ω, H u ω = K u ω) :
itoIntegralL2 P F B H t = itoIntegralL2 P F B K t
noncomputable def itoIntegralL2 (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Lp ℝ 2 P :=
if h : IsItoApproximable P F H t then
limUnder atTop fun n ↦ toL2 P ((h.2.choose n).itoIntegral B t)
else 0
MathlibExt/Probability/ItoIntegral.lean:118
Uses 11
TheoremElementary integrands are Itô-approximable#✓fully proved
An elementary integrand is Itô-approximable on every [0, t] (by itself).
theorem isItoApproximable_toProcess {F : Filtration ℝ≥0 mΩ} (P : Measure Ω)
(K : ElementaryIntegrand F) (t : ℝ≥0) : IsItoApproximable P F K.toProcess t
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
def IsItoApproximable (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
Prop :=
Measurable (fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2) ∧
∃ Hn : ℕ → ElementaryIntegrand F,
Tendsto (fun n ↦ integrandDist P (Hn n).toProcess H t) atTop (𝓝 0)
MathlibExt/Probability/ItoIntegral.lean:103
Uses 7
TheoremItô integral agrees with the elementary integral on elementary integrands#✓fully proved
On an elementary integrand, the Itô integral agrees almost surely with the elementary Itô integral.
theorem itoIntegral_toProcess_ae_eq {F : Filtration ℝ≥0 mΩ} {P : Measure Ω} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) (K : ElementaryIntegrand F) (t : ℝ≥0) :
itoIntegral P F B K.toProcess t =ᵐ[P] K.itoIntegral B t
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 12 · Used by 1
TheoremElementary integrands#✓fully proved
For a ≤ b and a bounded F a-measurable ξ, the Itô integral
of ξ 1_{(a, b]} against a pre-Brownian motion B adapted to F with increments independent
of the past is ξ (B (b ∧ t) - B (a ∧ t)) almost surely (Karatzas–Shreve 1991,
Section 3.2.A).
theorem itoIntegral_indicator_Ioc {F : Filtration ℝ≥0 mΩ} {P : Measure Ω} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) {a b : ℝ≥0} (hab : a ≤ b) {ξ : Ω → ℝ} (hξ : Measurable[F a] ξ) (C : ℝ)
(hξC : ∀ ω, |ξ ω| ≤ C) (t : ℝ≥0) :
itoIntegral P F B (fun u ω ↦ Set.indicator (Set.Ioc a b) (fun _ ↦ ξ ω) u) t =ᵐ[P]
fun ω ↦ ξ ω * (B (min b t) ω - B (min a t) ω)
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 7
Theorem\(L^2\) convergence of left-point approximations of a continuous function#✓fully proved
The left-point approximations of a continuous deterministic g converge to g in
L²(P ⊗ du) on (0, t] × Ω.
theorem tendsto_integrandDist_riemann {F : Filtration ℝ≥0 mΩ} {P : Measure Ω}
[IsProbabilityMeasure P] {g : ℝ → ℝ} (hg : Continuous g) (t : ℝ≥0) :
Tendsto (fun n ↦ integrandDist P (ElementaryIntegrand.riemann F g t n).toProcess
(fun u _ ↦ g u) t) atTop (𝓝 0)
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
noncomputable def riemann (F : Filtration ℝ≥0 mΩ) (g : ℝ → ℝ) (t : ℝ≥0) (n : ℕ) :
ElementaryIntegrand F where
n := n
time := fun k ↦ t * k / n
monotone_time := fun i j hij ↦ by
have : ((i : ℕ) : ℝ≥0) ≤ (j : ℕ) := by exact_mod_cast hij
dsimp only
gcongr
coeff := fun k _ ↦ g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)
measurable_coeff := fun _ ↦ measurable_const
bound := ∑ k : Fin n, |g ((t * (k.castSucc : ℕ) / n : ℝ≥0) : ℝ)|
abs_coeff_le := fun k _ ↦
⋯
MathlibExt/Probability/ItoRiemannSums.lean:171
Uses 5 · Used by 3
TheoremWiener's integration by parts#✓fully proved
For a Brownian motion B adapted to F with
increments independent of the past and a deterministic C¹ integrand g, the Itô integral is
∫_0^t g dB = g t B t - g 0 B 0 - ∫_0^t g'(u) B u du almost surely (Karatzas–Shreve 1991,
Section 3.3; the right side is a pathwise Riemann integral).
theorem itoIntegral_deterministic_eq {F : Filtration ℝ≥0 mΩ} {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) {g : ℝ → ℝ} (hg : ContDiff ℝ 1 g) (t : ℝ≥0) :
itoIntegral P F B (fun u _ ↦ g u) t =ᵐ[P]
fun ω ↦ g t * B t ω - g 0 * B 0 ω -
∫ u in (0 : ℝ)..t, deriv g u * B (Real.toNNReal u) ω
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 11 · Used by 1
C¹ integrand · Itô integral as an element of \(L^2\) · Itô integral process is a version of the \(L^2\) integral · Restriction to (0, t) preserves joint measurability · \(L^2\) convergence of left-point approximations of a continuous function · The Itô integral is well defined · Function as an element of \(L^2\)TheoremThe Ornstein–Uhlenbeck solution in Itô form#✓fully proved
For a Brownian motion B adapted to F
with increments independent of the past, any initial value X₀ and any real θ, σ, the Itô
form e^{-θt} X₀ + σ e^{-θt} ∫_0^t e^{θs} dB_s = e^{-θt} X₀ + σ ∫_0^t e^{-θ(t-s)} dB_s of the
solution of dX = -θ X dt + σ dB (Karatzas–Shreve 1991, Section 5.6) agrees almost surely with
the pathwise solution ouPathSolution, which solves X t = X₀ - θ ∫_0^t X + σ (B t - B 0) path
by path (ProbabilityTheory.ouPathSolution_integral_eq).
theorem ito_ou_solution_eq_ouPathSolution {F : Filtration ℝ≥0 mΩ} {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) (θ σ : ℝ) (X₀ : Ω → ℝ) (t : ℝ≥0) :
(fun ω ↦ exp (-θ * t) * X₀ ω +
σ * exp (-θ * t) * itoIntegral P F B (fun u _ ↦ exp (θ * u)) t ω) =ᵐ[P]
fun ω ↦ ouPathSolution θ σ (X₀ ω) (fun u ↦ B (Real.toNNReal u) ω) t
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
noncomputable def ouPathSolution (θ σ x₀ : ℝ) (w : ℝ → ℝ) (t : ℝ) : ℝ :=
exp (-θ * t) * x₀ +
σ * (w t - exp (-θ * t) * w 0 - θ * ∫ u in (0 : ℝ)..t, exp (-θ * (t - u)) * w u)
MathlibExt/Probability/OrnsteinUhlenbeck.lean:600
Uses 4
TheoremMeasurability of the \(L^2\) Itô integral#✓fully proved
The L² Itô integral is (almost surely equal to) an F t-measurable function.
theorem aestronglyMeasurable_itoIntegralL2 {F : Filtration ℝ≥0 mΩ} {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) {H : ℝ≥0 → Ω → ℝ} {t : ℝ≥0} (hH : IsItoApproximable P F H t) :
AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P
def IsItoApproximable (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
Prop :=
Measurable (fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2) ∧
∃ Hn : ℕ → ElementaryIntegrand F,
Tendsto (fun n ↦ integrandDist P (Hn n).toProcess H t) atTop (𝓝 0)
MathlibExt/Probability/ItoIntegral.lean:103
noncomputable def itoIntegralL2 (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Lp ℝ 2 P :=
if h : IsItoApproximable P F H t then
limUnder atTop fun n ↦ toL2 P ((h.2.choose n).itoIntegral B t)
else 0
MathlibExt/Probability/ItoIntegral.lean:118
Uses 11 · Used by 1
TheoremMartingale property of the Itô integral#✓fully proved
For a pre-Brownian motion B adapted to F
with increments independent of the past and an integrand H that is Itô-approximable on every
[0, t], the Itô integral t ↦ ∫_0^t H dB is an F-martingale (Karatzas–Shreve 1991,
Proposition 3.2.10).
theorem martingale_itoIntegral {F : Filtration ℝ≥0 mΩ} {P : Measure Ω} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) {H : ℝ≥0 → Ω → ℝ} (hH : ∀ t, IsItoApproximable P F H t) :
Martingale (itoIntegral P F B H) F P
def IsItoApproximable (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
Prop :=
Measurable (fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2) ∧
∃ Hn : ℕ → ElementaryIntegrand F,
Tendsto (fun n ↦ integrandDist P (Hn n).toProcess H t) atTop (𝓝 0)
MathlibExt/Probability/ItoIntegral.lean:103
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 15 · Used by 2
TheoremIntegrand distance as a squared \(L^2\) seminorm#✓fully proved
The integrand distance on (0, t] is the square of the L² seminorm on
Ω × (0, t].
theorem integrandDist_eq_eLpNorm_sq {P : Measure Ω} [IsFiniteMeasure P]
{X Y : ℝ≥0 → Ω → ℝ} {t : ℝ≥0}
(hX : Measurable fun p : ℝ × Ω ↦ restrictIoc X t p.1.toNNReal p.2)
(hY : Measurable fun p : ℝ × Ω ↦ restrictIoc Y t p.1.toNNReal p.2) :
integrandDist P X Y t = eLpNorm (fun p : Ω × ℝ ↦ X p.2.toNNReal p.1 - Y p.2.toNNReal p.1) 2
(P.prod (volume.restrict (Set.Ioc (0 : ℝ) t))) ^ 2
noncomputable def restrictIoc (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) (u : ℝ≥0) (ω : Ω) : ℝ :=
(Set.Ioc 0 t).indicator (fun v ↦ H v ω) u
MathlibExt/Probability/ItoIntegral.lean:97
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
Uses 3 · Used by 2
TheoremItô isometry#✓fully proved
Itô isometry for the L² Itô integral, in ℝ≥0∞ form: for a pre-Brownian motion B
adapted to F with increments independent of the past and an integrand H that is
Itô-approximable on [0, t], E[(∫_0^t H dB)²] = E ∫_0^t H_u² du (Karatzas–Shreve 1991,
Section 3.2).
theorem lintegral_itoIntegral_sq {F : Filtration ℝ≥0 mΩ} {P : Measure Ω} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) {H : ℝ≥0 → Ω → ℝ} {t : ℝ≥0} (hH : IsItoApproximable P F H t) :
∫⁻ ω, ‖itoIntegral P F B H t ω‖ₑ ^ 2 ∂P =
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω‖ₑ ^ 2) ∂P
def IsItoApproximable (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
Prop :=
Measurable (fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2) ∧
∃ Hn : ℕ → ElementaryIntegrand F,
Tendsto (fun n ↦ integrandDist P (Hn n).toProcess H t) atTop (𝓝 0)
MathlibExt/Probability/ItoIntegral.lean:103
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 15 · Used by 4
TheoremLebesgue differentiation along shrinking off-center intervals#✓fully proved
For a locally integrable
f : ℝ → ℝ, for almost every u, the averages of f over intervals [a n, b n] converge to
f u whenever the lengths b n - a n > 0 tend to 0 and the distance from u to the midpoint
of [a n, b n] is at most twice the length.
theorem MeasureTheory.LocallyIntegrable.ae_tendsto_average_Icc {f : ℝ → ℝ}
(hf : LocallyIntegrable f volume) :
∀ᵐ u, ∀ a b : ℕ → ℝ, (∀ᶠ n in atTop, a n < b n) →
(∀ᶠ n in atTop, |u - (a n + b n) / 2| ≤ 2 * (b n - a n)) →
Tendsto (fun n ↦ b n - a n) atTop (𝓝 0) →
Tendsto (fun n ↦ ⨍ x in Set.Icc (a n) (b n), f x) atTop (𝓝 (f u))
Used by 1
TheoremProgressive processes are jointly measurable#✓fully proved
A progressive process is jointly measurable in (u, ω) (reading u : ℝ through
Real.toNNReal).
theorem IsProgressive.measurable_toNNReal {F : Filtration ℝ≥0 mΩ} {H : ℝ≥0 → Ω → ℝ}
(hH : IsProgressive F H) : Measurable fun p : ℝ × Ω ↦ H p.1.toNNReal p.2
TheoremTruncation of a progressive process is progressive#✓fully proved
Truncating a progressive process at level M (Mathlib's ProbabilityTheory.truncation,
which keeps the values in (-M, M] and sets the others to 0) gives a progressive process.
theorem IsProgressive.truncation {F : Filtration ℝ≥0 mΩ} {H : ℝ≥0 → Ω → ℝ}
(hH : IsProgressive F H) (M : ℝ) : IsProgressive F (fun u ↦ truncation (H u) M)
Used by 1
TheoremMeasurability of time averages of a progressive process#✓fully proved
For a progressive H and b ≤ T, the average of u ↦ H u ω over [a, b] is
F T-measurable in ω.
theorem IsProgressive.measurable_average_Icc {F : Filtration ℝ≥0 mΩ} {H : ℝ≥0 → Ω → ℝ}
(hH : IsProgressive F H) {a b : ℝ} {T : ℝ≥0} (hbT : b ≤ T) :
Measurable[F T] fun ω ↦ ⨍ s in Set.Icc a b, H s.toNNReal ω
Used by 1
DefinitionDelayed-average approximation of a progressive process#✓fully proved
The delayed-average approximation of a progressive process H on [0, t], truncated at
level M, with n + 1 intervals: on (t_k, t_{k+1}], with t_k = k t / (n + 1), it equals the
average of truncation (H ·) M over [t_{k-1}, t_k] for k ≥ 1, and 0 for k = 0. For
M ≤ 0 the truncation, and hence the approximation, is 0.
ProbabilityTheory.delayedAverage · 23 lines
noncomputable def delayedAverage {F : Filtration ℝ≥0 mΩ} {H : ℝ≥0 → Ω → ℝ}
(hH : IsProgressive F H) (M : ℝ) (t : ℝ≥0) (n : ℕ) : ElementaryIntegrand F where
n := n + 1
time := fun i ↦ t * ((i : ℝ≥0) / (n + 1))
monotone_time := fun i j hij ↦ by
dsimp only
gcongr
exact_mod_cast hij
coeff := fun i ω ↦ if (i : ℕ) = 0 then 0 else
⨍ s in Set.Icc ((t : ℝ) * (((i : ℕ) : ℝ) - 1) / (n + 1)) ((t : ℝ) * ((i : ℕ) : ℝ) / (n + 1)),
truncation (H s.toNNReal) M ω
measurable_coeff := fun i ↦ by
by_cases hi : (i : ℕ) = 0
· simp only [hi, ↓reduceIte]
exact measurable_const
· simp only [hi, ↓reduceIte]
refine IsProgressive.measurable_average_Icc (IsProgressive.truncation hH M) ?_
simp [mul_div_assoc]
bound := |M|
abs_coeff_le := fun i ω ↦ by
split_ifs
· simp
· exact abs_average_Icc_le (fun x ↦ abs_truncation_le_bound _ M ω) _ _
structure ElementaryIntegrand (F : Filtration ℝ≥0 mΩ) where
/-- The number of partition intervals. -/
n : ℕ
/-- The partition times `time 0 ≤ time 1 ≤ ⋯ ≤ time n`. -/
time : Fin (n + 1) → ℝ≥0
/-- The partition times are nondecreasing. -/
monotone_time : Monotone time
/-- The coefficient on the interval `(time i, time (i + 1)]`. -/
coeff : Fin n → Ω → ℝ
/-- Each coefficient is known at the left end of its interval. -/
measurable_coeff : ∀ i, Measurable[F (time i.castSucc)] (coeff i)
/-- A uniform bound on the coefficients. -/
⋯
MathlibExt/Probability/ElementaryItoIntegral.lean:74
Uses 3 · Used by 2
TheoremConvergence of the delayed averages#✓fully proved
For a progressive H and a finite measure P, the
delayed-average approximations of the truncation of H at level M converge to it in
L²(P ⊗ du) on (0, t] × Ω as the mesh t / (n + 1) tends to 0 (Karatzas–Shreve 1991, proof of
Lemma 3.2.4(b)).
theorem tendsto_integrandDist_delayedAverage {P : Measure Ω} [IsFiniteMeasure P]
{F : Filtration ℝ≥0 mΩ} {H : ℝ≥0 → Ω → ℝ} (hH : IsProgressive F H) (M : ℝ) (t : ℝ≥0) :
Tendsto (fun n ↦ integrandDist P (delayedAverage hH M t n).toProcess
(fun u ↦ truncation (H u) M) t) atTop (𝓝 0)
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
noncomputable def delayedAverage {F : Filtration ℝ≥0 mΩ} {H : ℝ≥0 → Ω → ℝ}
(hH : IsProgressive F H) (M : ℝ) (t : ℝ≥0) (n : ℕ) : ElementaryIntegrand F where
n := n + 1
time := fun i ↦ t * ((i : ℝ≥0) / (n + 1))
monotone_time := fun i j hij ↦ by
dsimp only
gcongr
exact_mod_cast hij
coeff := fun i ω ↦ if (i : ℕ) = 0 then 0 else
⨍ s in Set.Icc ((t : ℝ) * (((i : ℕ) : ℝ) - 1) / (n + 1)) ((t : ℝ) * ((i : ℕ) : ℝ) / (n + 1)),
truncation (H s.toNNReal) M ω
measurable_coeff := fun i ↦ by
⋯
MathlibExt/Probability/ItoDensity.lean:176
Uses 8 · Used by 1
TheoremTruncation#✓fully proved
For a jointly measurable H with E ∫_0^t H_u² du < ∞, the truncations of
H at levels M → ∞ converge to H in L²(P ⊗ du) on (0, t] × Ω
(Karatzas–Shreve 1991, proof of Lemma 3.2.4(c)).
theorem tendsto_integrandDist_truncation {P : Measure Ω} {H : ℝ≥0 → Ω → ℝ}
(hHm : Measurable fun p : ℝ × Ω ↦ H p.1.toNNReal p.2) (t : ℝ≥0)
(hH2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
Tendsto (fun M : ℕ ↦ integrandDist P (fun u ↦ truncation (H u) M) H t) atTop (𝓝 0)
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
Uses 1 · Used by 1
TheoremDensity of elementary integrands#✓fully proved
A progressive integrand H with
E ∫_0^t H_u² du < ∞ is the L²(P ⊗ du)-limit on (0, t] × Ω of elementary integrands
(Karatzas–Shreve 1991, Lemma 3.2.4 and Proposition 3.2.6).
theorem isItoApproximable_of_isProgressive {P : Measure Ω} [IsFiniteMeasure P]
{F : Filtration ℝ≥0 mΩ} {H : ℝ≥0 → Ω → ℝ} (hH : IsProgressive F H) (t : ℝ≥0)
(hH2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
IsItoApproximable P F H t
def IsItoApproximable (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
Prop :=
Measurable (fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2) ∧
∃ Hn : ℕ → ElementaryIntegrand F,
Tendsto (fun n ↦ integrandDist P (Hn n).toProcess H t) atTop (𝓝 0)
MathlibExt/Probability/ItoIntegral.lean:103
Uses 12 · Used by 5
TheoremSquare integrability of the Itô integral#✓fully proved
The Itô integral at each time is square integrable: it is a version of the element
itoIntegralL2 P F B H t of L²(P) (which is 0 when H is not Itô-approximable).
theorem memLp_itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : MemLp (itoIntegral P F B H t) 2 P
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 3 · Used by 3
TheoremItô isometry for progressive integrands#✓fully proved
For a pre-Brownian motion B adapted to F
with increments independent of the past and an F-progressive integrand H with
E ∫_0^t H_u² du < ∞, E[(∫_0^t H dB)²] = E ∫_0^t H_u² du (Karatzas–Shreve 1991,
Section 3.2).
theorem lintegral_itoIntegral_sq_of_isProgressive {P : Measure Ω} {F : Filtration ℝ≥0 mΩ}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) {H : ℝ≥0 → Ω → ℝ} (hH : IsProgressive F H) (t : ℝ≥0)
(hH2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
∫⁻ ω, ‖itoIntegral P F B H t ω‖ₑ ^ 2 ∂P =
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω‖ₑ ^ 2) ∂P
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 3 · Used by 1
TheoremMartingale property for progressive integrands#✓fully proved
For a pre-Brownian motion B adapted
to F with increments independent of the past and an F-progressive integrand H with
E ∫_0^t H_u² du < ∞ for every t, the Itô integral t ↦ ∫_0^t H dB is an F-martingale
(Karatzas–Shreve 1991, Proposition 3.2.10).
theorem martingale_itoIntegral_of_isProgressive {P : Measure Ω} {F : Filtration ℝ≥0 mΩ}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P) {H : ℝ≥0 → Ω → ℝ} (hH : IsProgressive F H)
(hH2 : ∀ t : ℝ≥0, ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
Martingale (itoIntegral P F B H) F P
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 3
TheoremContinuous modification#✓fully proved
The Itô integral admits a modification with continuous paths:
there is a process J with continuous paths such that J t = ∫_0^t H dB almost surely for each
t (Karatzas–Shreve 1991, Section 3.2). ProbabilityTheory.itoIntegral chooses its version
separately at each time, so it is only determined up to a null set that may depend on t; the
statement therefore asks for a modification rather than for a process indistinguishable from
this particular choice. Any two continuous modifications are indistinguishable.
public theorem itoIntegral_continuous_modification {Ω : Type*} {mΩ : MeasurableSpace Ω}
{P : Measure Ω} {F : Filtration ℝ≥0 mΩ} {B : ℝ≥0 → Ω → ℝ} (hB : IsBrownianReal B P)
(hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P)
{H : ℝ≥0 → Ω → ℝ} (hH : IsProgressive F H)
(hH2 : ∀ t : ℝ≥0, ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t,
‖H u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
∃ J : ℝ≥0 → Ω → ℝ, (∀ ω, Continuous fun t ↦ J t ω) ∧
∀ t, J t =ᵐ[P] itoIntegral P F B H t
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 16
TheoremItô isometry for Itô-approximable integrands#✓fully proved
The squared L²(P ⊗ du) distance between two Itô-approximable integrands is the squared
L²(P) distance between their Itô integrals.
theorem integrandDist_eq_dist_sq_itoIntegralL2 {F : Filtration ℝ≥0 mΩ} {P : Measure Ω}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P) (hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep
(MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance) (F s) P)
{H K : ℝ≥0 → Ω → ℝ} {t : ℝ≥0} (hH : IsItoApproximable P F H t)
(hK : IsItoApproximable P F K t) :
integrandDist P H K t = ENNReal.ofReal
(dist (itoIntegralL2 P F B H t) (itoIntegralL2 P F B K t) ^ 2)
def IsItoApproximable (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (H : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) :
Prop :=
Measurable (fun p : ℝ × Ω ↦ restrictIoc H t p.1.toNNReal p.2) ∧
∃ Hn : ℕ → ElementaryIntegrand F,
Tendsto (fun n ↦ integrandDist P (Hn n).toProcess H t) atTop (𝓝 0)
MathlibExt/Probability/ItoIntegral.lean:103
noncomputable def integrandDist (P : Measure Ω) (H K : ℝ≥0 → Ω → ℝ) (t : ℝ≥0) : ℝ≥0∞ :=
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω - K u.toNNReal ω‖ₑ ^ 2) ∂P
MathlibExt/Probability/ItoIntegral.lean:92
noncomputable def itoIntegralL2 (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Lp ℝ 2 P :=
if h : IsItoApproximable P F H t then
limUnder atTop fun n ↦ toL2 P ((h.2.choose n).itoIntegral B t)
else 0
MathlibExt/Probability/ItoIntegral.lean:118
Uses 14 · Used by 2
TheoremLinearity (additivity)#✓fully proved
The Itô integral is additive in the integrand: for
F-progressive integrands H₁, H₂ with E ∫_0^t H_i² du < ∞, the integral of the sum is almost
surely the sum of the integrals. Together with homogeneity and the difference isometry this pins
down the integral on the whole L² space of progressive integrands. Only the pre-Brownian
finite-dimensional laws are used; path continuity is not required.
public theorem itoIntegral_add_of_isPreBrownianReal {Ω : Type*} {mΩ : MeasurableSpace Ω}
{P : Measure Ω} {F : Filtration ℝ≥0 mΩ} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P)
(hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P)
{H₁ H₂ : ℝ≥0 → Ω → ℝ} (hH₁ : IsProgressive F H₁) (hH₂ : IsProgressive F H₂) (t : ℝ≥0)
(hH₁2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H₁ u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞)
(hH₂2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H₂ u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
itoIntegral P F B (H₁ + H₂) t =ᵐ[P]
fun ω ↦ itoIntegral P F B H₁ t ω + itoIntegral P F B H₂ t ω
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 11 · Used by 2
TheoremLinearity (additivity)#✓fully proved
The Itô integral is additive in the integrand: for
F-progressive integrands H₁, H₂ with E ∫_0^t H_i² du < ∞, the integral of the sum is almost
surely the sum of the integrals. Together with homogeneity and the difference isometry this pins
down the integral on the whole L² space of progressive integrands.
public theorem itoIntegral_add {Ω : Type*} {mΩ : MeasurableSpace Ω}
{P : Measure Ω} {F : Filtration ℝ≥0 mΩ} {B : ℝ≥0 → Ω → ℝ} (hB : IsBrownianReal B P)
(hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P)
{H₁ H₂ : ℝ≥0 → Ω → ℝ} (hH₁ : IsProgressive F H₁) (hH₂ : IsProgressive F H₂) (t : ℝ≥0)
(hH₁2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H₁ u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞)
(hH₂2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H₂ u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
itoIntegral P F B (H₁ + H₂) t =ᵐ[P]
fun ω ↦ itoIntegral P F B H₁ t ω + itoIntegral P F B H₂ t ω
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 2
TheoremLinearity (homogeneity)#✓fully proved
The Itô integral is homogeneous in the integrand for a pre-Brownian integrator; path continuity is not required.
public theorem itoIntegral_smul_of_isPreBrownianReal {Ω : Type*} {mΩ : MeasurableSpace Ω}
{P : Measure Ω} {F : Filtration ℝ≥0 mΩ} {B : ℝ≥0 → Ω → ℝ}
(hB : IsPreBrownianReal B P)
(hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P)
{H : ℝ≥0 → Ω → ℝ} (hH : IsProgressive F H) (a : ℝ) (t : ℝ≥0)
(hH2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
itoIntegral P F B (a • H) t =ᵐ[P] fun ω ↦ a * itoIntegral P F B H t ω
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 9 · Used by 2
TheoremLinearity (homogeneity)#✓fully proved
The Itô integral is homogeneous in the integrand.
public theorem itoIntegral_smul {Ω : Type*} {mΩ : MeasurableSpace Ω}
{P : Measure Ω} {F : Filtration ℝ≥0 mΩ} {B : ℝ≥0 → Ω → ℝ} (hB : IsBrownianReal B P)
(hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P)
{H : ℝ≥0 → Ω → ℝ} (hH : IsProgressive F H) (a : ℝ) (t : ℝ≥0)
(hH2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
itoIntegral P F B (a • H) t =ᵐ[P] fun ω ↦ a * itoIntegral P F B H t ω
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 2
TheoremDifference isometry#✓fully proved
For two F-progressive integrands with E ∫_0^t H_i² du < ∞, the
difference of the integrals is square-integrable and
E[(∫ H₁ dB - ∫ H₂ dB)²] = E ∫ (H₁ - H₂)² du. With linearity this is the two-integrand isometry
that, together with the elementary-integrand formula, determines the construction on the whole
L² space. Only the pre-Brownian finite-dimensional laws are used; path continuity is not
required.
public theorem itoIntegral_isometry_sub_of_isPreBrownianReal {Ω : Type*}
{mΩ : MeasurableSpace Ω} {P : Measure Ω} {F : Filtration ℝ≥0 mΩ}
{B : ℝ≥0 → Ω → ℝ} (hB : IsPreBrownianReal B P)
(hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P)
{H₁ H₂ : ℝ≥0 → Ω → ℝ} (hH₁ : IsProgressive F H₁) (hH₂ : IsProgressive F H₂) (t : ℝ≥0)
(hH₁2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H₁ u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞)
(hH₂2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H₂ u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
MemLp (fun ω ↦ itoIntegral P F B H₁ t ω - itoIntegral P F B H₂ t ω) 2 P ∧
∫⁻ ω, ‖itoIntegral P F B H₁ t ω - itoIntegral P F B H₂ t ω‖ₑ ^ 2 ∂P =
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t,
‖H₁ u.toNNReal ω - H₂ u.toNNReal ω‖ₑ ^ 2) ∂P
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 8 · Used by 1
TheoremDifference isometry#✓fully proved
For two F-progressive integrands with E ∫_0^t H_i² du < ∞, the
difference of the integrals is square-integrable and
E[(∫ H₁ dB - ∫ H₂ dB)²] = E ∫ (H₁ - H₂)² du. With linearity this is the two-integrand isometry
that, together with the elementary-integrand formula, determines the construction on the whole
L² space.
public theorem itoIntegral_isometry_sub {Ω : Type*} {mΩ : MeasurableSpace Ω}
{P : Measure Ω} {F : Filtration ℝ≥0 mΩ} {B : ℝ≥0 → Ω → ℝ} (hB : IsBrownianReal B P)
(hBF : Adapted F B)
(hInd : ∀ s t, s ≤ t → Indep (MeasurableSpace.comap (fun ω ↦ B t ω - B s ω) inferInstance)
(F s) P)
{H₁ H₂ : ℝ≥0 → Ω → ℝ} (hH₁ : IsProgressive F H₁) (hH₂ : IsProgressive F H₂) (t : ℝ≥0)
(hH₁2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H₁ u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞)
(hH₂2 : ∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t, ‖H₂ u.toNNReal ω‖ₑ ^ 2) ∂P ≠ ∞) :
MemLp (fun ω ↦ itoIntegral P F B H₁ t ω - itoIntegral P F B H₂ t ω) 2 P ∧
∫⁻ ω, ‖itoIntegral P F B H₁ t ω - itoIntegral P F B H₂ t ω‖ₑ ^ 2 ∂P =
∫⁻ ω, (∫⁻ u in Set.Ioc (0 : ℝ) t,
‖H₁ u.toNNReal ω - H₂ u.toNNReal ω‖ₑ ^ 2) ∂P
noncomputable def itoIntegral (P : Measure Ω) (F : Filtration ℝ≥0 mΩ) (B H : ℝ≥0 → Ω → ℝ)
(t : ℝ≥0) : Ω → ℝ :=
if h : AEStronglyMeasurable[F t] (itoIntegralL2 P F B H t) P then h.mk _
else itoIntegralL2 P F B H t
MathlibExt/Probability/ItoIntegral.lean:128
Uses 2
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