Kallenberg Chain Lemma for Reverse Filtration #
This file implements the core "Kallenberg chain" step from page 28 of Kallenberg (2005).
Main Results #
pair_law_shift_eq_of_contractable- For contractable X with k < m ≤ n:(X k, shiftRV X m) =^d (X k, shiftRV X n)condExp_indicator_revFiltration_eq_of_le- The main Kallenberg chain lemma: For contractable X with k < m ≤ n and measurable B:μ[(B.indicator 1) ∘ X k | revFiltration X m] =ᵐ[μ] μ[(B.indicator 1) ∘ X k | revFiltration X n]
Mathematical Background #
Kallenberg's argument (page 28):
For a contractable sequence ξ with k < m ≤ n:
P[ξ_k ∈ B | θ_m ξ] = P[ξ_k ∈ B | θ_n ξ] (a.s.)
where θ_m ξ = (ξ_m, ξ_{m+1}, ...) is the m-shifted sequence.
Proof ingredients:
- Contractability → pair law:
(ξ_k, θ_m ξ) =^d (ξ_k, θ_n ξ)(same strictly increasing subsequence) σ(θ_n ξ) ⊆ σ(θ_m ξ)when m ≤ n (revFiltration_antitone)- Kallenberg Lemma 1.3 (
condExp_indicator_eq_of_law_eq_of_comap_le)
Notation #
In Kallenberg's notation:
shiftRV X m= θ_m ξ (the m-shifted sequence)revFiltration X m= σ(θ_m ξ) (the reverse filtration)tailSigma X= T_ξ (the tail σ-algebra)
References #
- Kallenberg (2005), Probabilistic Symmetries and Invariance Principles, page 28
Pair Law for Shifted Sequences #
For contractable X with k < m ≤ n, the pairs (X k, shiftRV X m) and (X k, shiftRV X n) have the same distribution. This follows from contractability by viewing each pair as a strictly increasing subsequence of X.
Embedding of α × (ℕ → α) into ℕ → α by placing the first element at position 0
and the sequence at positions 1, 2, 3, ...
Equations
Instances For
The injection k, m, m+1, m+2, ... for pair law argument.
This is strictly increasing when k < m.
Equations
Instances For
The pair (X k, shiftRV X m) factors through embedPairSeq and reindexing.
Pair law for shifted sequences from contractability.
For contractable X with k < m ≤ n, the pairs (X k, shiftRV X m) and (X k, shiftRV X n)
have the same distribution.
Proof: Both pairs correspond to strictly increasing subsequences of X:
(X k, shiftRV X m)corresponds to indicesk, m, m+1, m+2, ...(X k, shiftRV X n)corresponds to indicesk, n, n+1, n+2, ...
By contractability, these have equal finite marginals, hence equal measures.
Main Kallenberg Chain Lemma #
Using the pair law and the contraction structure σ(shiftRV X n) ⊆ σ(shiftRV X m), we apply Kallenberg Lemma 1.3 to drop from revFiltration X m to revFiltration X n.
Kallenberg Chain Lemma.
For contractable X with k < m ≤ n and measurable B:
μ[(B.indicator 1) ∘ X k | revFiltration X m] =ᵐ[μ] μ[(B.indicator 1) ∘ X k | revFiltration X n]
This is Kallenberg's key observation (page 28): conditioning X_k on the finer σ-algebra σ(θ_n ξ) gives the same result as conditioning on the coarser σ(θ_m ξ).
Proof:
(X k, shiftRV X m) =^d (X k, shiftRV X n)bypair_law_shift_eq_of_contractablerevFiltration X n ≤ revFiltration X mbyrevFiltration_antitone- Apply Kallenberg Lemma 1.3 (
condExp_indicator_eq_of_law_eq_of_comap_le)
Trivial case: k = m. X_m is measurable w.r.t. revFiltration X m (as (shiftRV X m) 0), so conditional expectation equals the function itself.
Convergence to Tail σ-algebra #
Using the Kallenberg chain lemma and reverse martingale convergence, we show that conditional expectations on revFiltration X m equal those on the tail σ-algebra.
Conditional expectation on revFiltration equals tail.
For contractable X with k < m, the conditional expectation of the indicator 1_{X_k ∈ B} given revFiltration X m equals the conditional expectation given tailSigma X.
Proof:
- By
condExp_indicator_revFiltration_eq_of_le, the sequenceμ[φ | revFiltration X n]is constant for n ≥ m. - By
condExp_tendsto_iInf, this sequence converges a.e. toμ[φ | tailSigma X]. - A constant sequence converges to its value, so the value equals the limit.