This work presents an evolutionary solution that aims to test the influence of the choice of numeraire on financial time series modeling. In particular, the method used in such a problem is to apply a very powerful natural computing analysis tool, namely evolutionary neural networks, based on the joint evolution of the topology and the connection weights together with a novel similarity-based crossover, to a couple of very liquid financial time series expressed in their trading currency and several alternative numeraires like gold, silver, and a currency like the euro, which is intended to be stable 'by design', and compare the results. © 2011 Springer-Verlag.
CITATION STYLE
Azzini, A., Dragoni, M., & Tettamanzi, A. G. B. (2011). Using evolutionary neural networks to test the influence of the choice of numeraire on financial time series modeling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6625 LNCS, pp. 81–90). https://doi.org/10.1007/978-3-642-20520-0_9
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