Abstract
We investigate the correlations among the intraday prices of the major stocks of the Milan Stock Exchange by means of a neuro-evolutionary modeling method. In particular, the method used to approach such 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 the analysis of a financial intraday time series expressing the stock quote variations of the FTSE MIB components. We show that it is possible to obtain extremely accurate models of the variations of the price of one stock based on the price variations of the other components of the stock list, which may be used for statistical arbitrage. © 2012 Springer-Verlag.
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Azzini, A., Dragoni, M., & Tettamanzi, A. G. B. (2012). A neuro-evolutionary approach to intraday financial modeling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7248 LNCS, pp. 155–164). https://doi.org/10.1007/978-3-642-29178-4_16
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