Abstract. Let L be a linear space of real random variables on the measurable space (Ω, A). Conditions for the existence of a probability P on A such that
Testo completo
Example 2. (Equivalent martingale measures). Let S = (S t : t ∈ I) be a real stochastic process, indexed by I ⊂ R, on the probability space (Ω, A, P 0 ). Suppose S is adapted to a filtration G = (G t : t ∈ I) and S t0
X(ω 1 , ω 2 ) = f (ω 1 ) − E Q1
To prove (4), fix a net (P α ) ⊂ Z converging to P ∈ Z, that is, P (A) = lim α P α (A) for all A ∈ A. If P α ∈ K for each α, then P ∈ P and (1/t) Q ≤ P ≤ t Q. Hence P ∈ K, that is, K is closed. Since Z is compact, K is actually compact. If P α ∈ K and E Pα
|E P (X)| = |E P (X) − E Pα
≤ |E P X − X I Ab
≤ E P |X| I {|X|>b} + |E P X I Ab
≤ 2 t E Q |X| I {|X|>b} + |E P X I Ab
Since X I Ab
for all i ∈ I. This concludes the proof if A = Ω. If A 6= Ω, just apply the above argument with A in the place of Ω. Then, there is a σ-additive probability P A on the trace σ-field σ(L) ∩ A such that E PA
E P (X) = E PA
(5) (X i1
subsets of Ω of the form {(X i1
some i 1 , . . . , i n , j 1 , . . . , j m ∈ I and some Borel sets B ⊂ R n and D ⊂ R m . Define Y = (X i1
K = {(f i1
K ∩ {(f i1
Q (f i1
= Q K ∩ {(f j1
P 0 (X i1
E P0
E P0
E P0
Theorem 14. Suppose E P0
P 0 (f > 0) = 1. Given X ∈ L, since E P (X + ) = E P (X − ), one also obtains E P0
≤ n E P (X + ) = n E P (X − ) ≤ k n E P0
Conversely, suppose condition (7) holds for some k n ≥ 0 and A n ∈ A such that lim n P 0 (A n ) = 1. If there is a subsequence n j such that k nj
E P0
k n 2 n ≤ k E P0
In particular, Q(A) ≤ k P 0 (A) and E Q |X| ≤ k E P0
E P0
k n 2 n ≤ k E P0
If P ∈ K, then E P |X| ≤ E Q |X| + k E P0
f = E Q (X) I {X<0} + E P0
E Q (X) P 0 (X < 0) + E P0
Since E Q (X) ≤ k E P0
E Q (X) P 0 (X < 0) + E P0
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