Let (Ω,F,P) be a probability space, let a,b be real numbers with 0≤a<b, let m≥1 be a natural number, and let W=(W1,…,Wm) be an m-dimensional Brownian motion. Let y,z be square-integrable random variables, let (αt)t∈[a,b] and (βt)t∈[a,b] be mean-square continuous families, and let fj,hj:[a,b]→R (1≤j≤m) be continuous.
Convention. For a continuous function g:[a,b]→R, a component index j∈{1,…,m}, and t∈[a,b], write
∫atgdWj:=∫0tg0dWj−∫0ag0dWj,
where g0 denotes the extension of g to [0,b] by the constant value g(a) on [0,a], and the right-hand integrals are Wiener integrals (for a=0 this is the usual Wiener integral, and in every case ∫aagdWj=0 by the convention of Ito Integrable Process and the Ito Integral). This convention applies below to fj, to hj, and to the function f of claim 2.
Fix versions of the mean-square Riemann integrals and Wiener integrals below and set, for t∈[a,b],
Yt=y+∫atαrdr+j=1∑m∫atfj(r)dWrj,Zt=z+∫atβrdr+j=1∑m∫athj(r)dWrj.
Then (Yt) and (Zt) are mean-square continuous families, with Ya=y and Za=z almost surely.
1. (Second-moment evolution) Suppose the orthogonality hypothesis: for every j∈{1,…,m} and all a≤s<t≤b, with the covariance,
Cov(∫atfjdWj−∫asfjdWj, Zs)=0andCov(∫athjdWj−∫ashjdWj, Ys)=0.
Then, with the expectation, the function t↦E[YtZt] is continuous on [a,b], the integrand below is continuous, and, with the Riemann integral,
E[YtZt]=E[yz]+∫at(E[αrZr]+E[Yrβr]+j=1∑mfj(r)hj(r))dr(a≤t≤b).
2. (Verification of the hypothesis in independent-input models) Let l≥1 be a natural number and ξ=(ξ1,…,ξl) a tuple of square-integrable random variables with σ(ξ1,…,ξl) independent of σ(Wtj′:1≤j′≤m, t≥0), with the generated σ-algebras. Fix a component index j∈{1,…,m}, reals a≤s<t≤b, and a continuous function f:[a,b]→R. If a square-integrable random variable Q is a limit, in the mean-square norm of Square-Integrable Random Variables and the Mean-Square Inner Product, of finite linear combinations of the constant 1, of the components ξi (1≤i≤l), and of the values Wrj′ (1≤j′≤m, 0≤r≤s), then
Cov(∫atfdWj−∫asfdWj, Q)=0.