05931072

a

05931072 Azzini, Antonia Dragoni, Mauro Tettamanzi, Andrea G.B. Using evolutionary neural networks to test the influence of the choice of numeraire on financial time series modeling. Di Chio, Cecilia (ed.) et al., Applications of evolutionary computation. EvoApplications 2011: EvoCOMNET, EvoFIN, EvoHOT, EvoMUSART, EvoSTIM, and EvoTRANSLOG, Torino, Italy, April 27--29, 2011. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-20519-4/pbk). Lecture Notes in Computer Science 6625, 81-90 (2011). 2011 Berlin: Springer EN

doi:10.1007/978-3-642-20520-0_9

Summary: 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.