Sequential optimizing investing strategy with neural networks

Ryo Adachi and Akimichi Takemura

Papers from arXiv.org

Abstract: In this paper we propose an investing strategy based on neural network models combined with ideas from game-theoretic probability of Shafer and Vovk. Our proposed strategy uses parameter values of a neural network with the best performance until the previous round (trading day) for deciding the investment in the current round. We compare performance of our proposed strategy with various strategies including a strategy based on supervised neural network models and show that our procedure is competitive with other strategies.

Date: 2010-02
New Economics Papers: this item is included in nep-cmp, nep-cse and nep-gth
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Published in Expert Systems with Applications 38 (2011) 12991-12998

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1002.2265

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