By S Goldberg
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This is easy, since Lt ∆Vt = Lt Ht0 , ∆St = Lt Ht0 , ∆St ∈ K(S) by definition of K(S). This shows that K(S ext ) = K(S). 2. Fix 0 ≤ t ≤ T , and let f ∈ K(S) = K(S ext ) be Ft -measurable. Then the random variable Vft is of the form VfT where f ∈ K(S). Proof. Clearly f f 1 − = Vt VT VT f VT − Vt Vt = 1 VT T s=t+1 f (Vs − Vs−1 ) . Vt T We see that f = s=t+1 Vft (Vs − Vs−1 ) belongs to K(S ext ) because Vft is Ft -measurable and the summation is on s > t. Hence f = f + f does the job. 3. 10). Then K(X) = f VT f ∈ K(S) .
M ) ∈ RM +. Writing y = η1 + · · · + ηM , µm = ηm y , µ = (µ1 , . . , µM ) and M Qµ = µm Qm , m=1 µ note that, when (η1 , . . , ηM ) runs trough RM + , the pairs (y, Q ) run through a R + × M (S). Hence we may write the Lagrangian as L(ξ1 , . . 26) + yx, where ξn ∈ dom(U ), y > 0, Q = (q1 , . . , qN ) ∈ Ma (S). 5), the only difference now being that Q runs through the set Ma (S) instead of being a fixed probability measure. Defining again Φ(ξ1 , . . , ξn ) = inf y>0,Q∈Ma (S) L(ξ1 , . .
D r−d u = u−d and defining Q[g] = q and Q[b] = 1 − q = u− = Letting q = u− d d u−r u−d we obtain the unique martingale measure Q for the process S. α Consider the utility function U (x) = xα for α ∈] − ∞, 1[\{0} with conβ α . 3 below). 1) by applying the duality theory developed above. Well, this is shooting with canons on pigeons, but we find it instructive to do some explicit calculations exemplifying the abstract formulae. The dual value function v(y) = E V y dQ dP , y > 0, equals 1 1 V (y2q) + V (y2(1 − q)) 2 2 = cV V (y), v(y) = where 1 β (2q)β + (2(1 − q)) .