Abstract
In this chapter we discuss the use of Elastic Maps as support tool in the decision process underlying the selection, optimization, and management of financial portfolios. In particular, we suggest an allocation scheme which is entirely driven by Elastic Maps, in contrast to the traditional model where investors distribute their money among assets chosen according to the mean and variance of their returns. Our optimization procedure is based on the selection of assets from clusters originated by the maps, according to the nodes proximity; this, in turn, is the criterion thanks to which we assign the proper weight to each asset into the portfolio. In order to check the profitability of the approach, we have empirically tested the method with stocks building the European STOXX 600 index that in turn has been used as performance benchmark.
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- 1.
MiFID has been applied in Italy by the Legislative Decree 164/2007, November 1, 2007.
- 2.
Although asset is a generic expression that can be used to indicate every kind of market financial instrument, we assume to refer to stocks.
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© 2016 Springer International Publishing Switzerland
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Resta, M. (2016). Elastic Maps to Define the Risk Profile of Financial Investments. In: Computational Intelligence Paradigms in Economic and Financial Decision Making. Intelligent Systems Reference Library, vol 99. Springer, Cham. https://doi.org/10.1007/978-3-319-21440-5_5
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DOI: https://doi.org/10.1007/978-3-319-21440-5_5
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-21439-9
Online ISBN: 978-3-319-21440-5
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