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Iterative nonparametric estimation of a log-optimal portfolio selection function

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2 Author(s)
H. Walk ; Math. Inst. A, Stuttgart Univ., Germany ; S. Yakowitz

Let stock market vectors form a stationary ergodic sequence. For fixed d ∈ N, a log-optimal portfolio selection function of the past d observed vectors is iteratively estimated on the basis of a training sequence by use of gradients and nonparametric regression. Strong consistency is obtained under a boundedness and α-mixing condition without further assumptions on the distribution

Published in:

IEEE Transactions on Information Theory  (Volume:48 ,  Issue: 1 )