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Elementary Ito integrals do not depend on step representation

Statement

Assume the Axiom of Choice and the standing hypothesis (H) of Elementary predictable Brownian integrands. Let H and H be two elementary predictable integrands on [0,T] whose values agree (dtP)-almost everywhere, and let It(H), It(H) be their defining sums Ito integral of an elementary predictable process for the chosen representations. Then IT(H)=IT(H) almost surely, and in fact It(H)=It(H) almost surely for every deterministic t[0,T]. In particular, replacing a representation by a deterministic refinement of its partition, or by any other elementary representation of the same (dtP)-class, does not change the sums; the elementary integral is a function of that class.

Facts & Assumptions

Given: AC, the standing hypothesis (H), a horizon T>0, elementary representations Hs=k=0m1ξk1(tk,tk+1](s) and Hs=l=0m1ξl1(ul,ul+1](s) with bounded coefficients measurable at the left endpoints, agreeing (dtP)-almost everywhere, and their defining sums.

[F1]

A (dtP)-almost-everywhere equality of two elementary processes, each predictable and hence product measurable, may be integrated by Tonelli: 0TΩHHdPdt=0. Tonelli's theorem for nonnegative measurable functions on a sigma-finite product Elementary predictable Brownian integrands

[F2]

For 0s<t the increment BtBs is independent of Fs, has law N(0,ts), mean 0 and second moment ts. Elementary predictable Brownian integrands Brownian covariance is equivalent to independent stationary normal increments Gaussian even moments for Brownian increments

[F3]

If YL1(P) is independent of a sub-sigma-algebra G, then E[YG]=EY almost surely: the constant EY is G-measurable, and for AG the factorization of expectations for the independent pair (Y,1A) gives E[Y1A]=EYP(A). Independent sigma-algebras and independent events Expectations factor over finite products of independent random variables Conditional expectation is unique almost surely

[F4]

For integrable Z and HG, E[E[ZG]H]=E[ZH] almost surely. If WL1, Z is G-measurable, and both ZW and ZE[WG] are integrable, then E[ZWG]=ZE[WG]. Tower property of conditional expectation Taking out what is known

[F5]

The defining sums are linear under a common refinement and I0(H)=0; adaptedness and path continuity are part of the definition. Ito integral of an elementary predictable process

[F6]

AC is declared for the conditional-expectation interface. The Axiom of Choice

Proof

technique · direct
1.1

Let 0=w0<w1<<wJ=T be the common refinement of the two partitions, and write Hs=j=0J1ηj1(wj,wj+1](s) and Hs=j=0J1ηj1(wj,wj+1](s), where ηj is the coefficient ξk of the block containing (wj,wj+1] and similarly for ηj; then ηj and ηj are bounded and Fwj-measurable, because FtkFwj whenever tkwj.

F5given
1.2

On each time interval the difference is the constant random variable ηjηj: HH=j(ηjηj)1(wj,wj+1] identically on [0,T], so Tonelli gives 0=0T ⁣ ⁣ΩHHdPdt=j=0J1(wj+1wj)Eηjηj. Every summand is nonnegative, wj+1wj>0, and therefore Eηjηj=0, that is, ηj=ηj almost surely for each j.

F1given
2.1

On the common refinement the elementary sum of item 5 can be taken over the refined partition: within each original block the increments telescope, j:(wj,wj+1](tk,tk+1]ξk(Bwj+1Bwj)=ξk(Btk+1Btk), a finite rearrangement of the defining sum. Applying this to H and to H, the difference of the two terminal sums is D:=IT(H)IT(H)=j=0J1(ηjηj)(Bwj+1Bwj) identically.

F5step 1.1
3.1

Write ζj:=ηjηj and Δj:=Bwj+1Bwj for each j. By [F2] the increment Δj is independent of Fwj and has law N(0,wj+1wj). Hence [F3] gives E[ΔjFwj]=0 and E[Δj2Fwj]=wj+1wj almost surely, because these conditional expectations of a variable independent of Fwj equal its unconditional mean. Since ζj is bounded and Fwj-measurable, [F4] yields E[ζjΔjFwj]=ζjE[ΔjFwj]=0 and E[ζj2Δj2Fwj]=ζj2(wj+1wj) almost surely.

F2F3F4step 2.1
4.1

Expanding the square, ED2=j,j=0J1E[ζjζjΔjΔj]. If j<j, then ζjΔjζj is Fwj-measurable and integrable, so the tower property and step 3.1 give E[ζjζjΔjE[ΔjFwj]]=0; by symmetry every off-diagonal term vanishes. The diagonal terms satisfy E[ζj2Δj2]=E[E[ζj2Δj2Fwj]]=E[ζj2](wj+1wj) by step 3.1.

F4step 3.1
5.1

Combining steps 4.1 and 1.2, ED2=j=0J1E[ζj2](wj+1wj)maxjζjj=0J1(wj+1wj)Eζj=0, where the last identity is the Tonelli computation of step 1.2. Since D is square-integrable, ED2=0 forces D=0 almost surely.

step 1.2step 4.1
6.1

The same computation at a deterministic time t[0,T] uses the truncated common partition {wjt}: its nonempty blocks are (wj,wj+1t] with wj<t, whose left endpoints are wj and whose coefficients ζj are Fwj-measurable, so the truncated sum is elementary; the difference of the truncated sums is jζj(Bwj+1tBwjt), each increment is independent of Fwj with second moment (wj+1t)(wjt), and the off-diagonal terms vanish by the same tower argument. The diagonal sum is jE[ζj2]((wj+1t)(wjt))maxjζjjEζj((wj+1t)(wjt)), and this is 0 by the Tonelli identity of step 1.2 restricted to [0,t]. Hence It(H)=It(H) almost surely for every t. A deterministic refinement of one partition is the special case in which the two representations are identically equal, and then the shared coefficients cancel in ζj, recovering that refinement changes nothing. AC enters only through the conditional-expectation facts [F3] and [F4]; the grid, the coefficients and the limits in the argument are all determined by the given representations.

step 5.1F2F4F6given

Source notes

Van der Vaart, Definition 5.20 and Lemma 5.22, first defines the integral on step processes and then checks that the definition does not depend on the representation; the isometry computation for the difference is the same conditional-centering expansion used here. The nearly-sure statement at every fixed time is what makes the notation 0tHdB well defined before the completion step of item 10.

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Cited to discharge well-definedness by Ito integral of an elementary predictable process.

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