(a) Let (Xt)t≥o be a stochastic process defined by f fr dWr, t≥0, D where W = (Wr)rzo is a Wiener martingale and fE H. Prove rt^s € Cov(X§, Xt) = E(X¸Xt) = E [^³ f² dr, for any s,t = [0, ∞), where s ^ t = min(s, t).

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(a) Let (X{)t>o be a stochastic process defined by
fr dW,,
t > 0,
where W = (W,)r>o_is a Wiener martingale and f € H. Prove
rt^s
Cov(X3, X4) = E(X,X;) = E f; dr,
for any s,t e [0, 0),
S-
where s At = min(s,t).
Transcribed Image Text:(a) Let (X{)t>o be a stochastic process defined by fr dW,, t > 0, where W = (W,)r>o_is a Wiener martingale and f € H. Prove rt^s Cov(X3, X4) = E(X,X;) = E f; dr, for any s,t e [0, 0), S- where s At = min(s,t).
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