A Portfolio Diversification Strategy via Tail Dependence Clustering
| Autor: | Fabrizio Durante, Roberta Pappadà, Enrico Foscolo, Hao Wang |
|---|---|
| Přispěvatelé: | Maria Brigida Ferraro, Paolo Giordani, Barbara Vantaggi, Marek Gagolewski, María Ángeles Gil, Przemysław Grzegorzewski, Olgierd Hryniewicz, Wang, Hao, Pappada', Roberta, Durante, Fabrizio, Foscolo, Enrico, Ferraro, MB, Giordani, P, Vantaggi, B, Gagolewski, M, Gil, MA, Grzegorzewski, P, Hryniewicz, O, Pappada' , Roberta |
| Rok vydání: | 2016 |
| Předmět: |
050208 finance
Financial economics Computer Science (all) 05 social sciences Diversification (finance) Tail dependence Portfolio composition 01 natural sciences 010104 statistics & probability Control and Systems Engineering 0502 economics and business Econometrics Economics Portfolio 0101 mathematics Cluster analysis |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783319429717 SMPS |
| DOI: | 10.1007/978-3-319-42972-4_63 |
| Popis: | We provide a two-stage portfolio selection procedure in order to increase the diversification benefits in a bear market. By exploiting tail dependence-based risky measures, a cluster analysis is carried out for discerning between assets with the same performance in risky scenarios. Then, the portfolio composition is determined by fixing a number of assets and by selecting only one item from each cluster. Empirical calculations on the EURO STOXX 50 prove that investing on selected assets in trouble periods may improve the performance of risk-averse investors. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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