Abstract
The currency arbitrage detection is to find a proper currency conversion sequence that can make the most currency arbitrage. In this paper, the currency arbitrage detection is described as a energy function. And then a Lotka-Volterra (LV) recurrent neural network (RNN) is proposed to obtain the minimum points of the energy function. Simulations demonstrate that the proposed LV RNN is a practical and effective model for the currency arbitrage detection.
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Zhang, Z. (2012). A Neural Network Model for Currency Arbitrage Detection. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31346-2_8
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DOI: https://doi.org/10.1007/978-3-642-31346-2_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31345-5
Online ISBN: 978-3-642-31346-2
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