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A combined clustering and multi-criteria approach for portfolio selection

digital A combined clustering and multi-criteria approach for portfolio selection
Article
journal STATISTICA & APPLICAZIONI
issue STATISTICA & APPLICAZIONI - 2019 - 1
title A combined clustering and multi-criteria approach for portfolio selection
authors


publisher Vita e Pensiero
format Article | Pdf
online since 08-2020
doi 10.26350/999999_000018
issn 18246672 (print)
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One of the key role of a portfolio manager is to identify a suitable asset allocation strategy. The portfolio composition task has to take into account the return and the risk of each asset along with several other factors such as investor’s aims, market expectations and risk tolerance. Thus the final decision making can be naturally viewed as a multiple criteria problem whose solution can benefit from Multiple Criteria Decision Making strategies. In this paper, we propose a two-step multi-criteria approach to support the selection of equity portfolios. Our strategy exploits a varying-coefficient Capital Asset Pricing Model framework. First, we identify clusters of stocks having similar systematic risk factors, then we rank these assets using an ELECTRE III method. We also present a real data example on stocks of S&P500 to illustrate the proposed methodology.

keywords

MCDM, P-Spline, Time Series, CAPM, Time-Varying Beta.

Authors biography

Dipartimento di Ingegneria industriale - Universita` di Napoli Federico II - Piazzale Tecchio 80 - 80125 NAPOLI (e-mail: carmela.iorio@unina.it, giuseppe.pandolfo@unina.it); Lead data scientist, Features-Analytics - S.A. 2 rue de Charleroi, 1400 NIVELLES - Belgium (e-mail: gianluca.frasso@features-analyitics.com); Dipartimento di Economia e statistica - Universita` di Napoli Federico II - Cupa Nuova Cintia, 21 - 80126 NAPOLI (e-mail: antdambr@unina.it).