Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-42972-4_63 | SOFT METHODS FOR DATA SCIENCE |
Field | DocType | Volume |
Financial economics,Tail dependence,Diversification (finance),Computer science,Portfolio,Diversification (marketing strategy),Cluster analysis | Conference | 456 |
ISSN | Citations | PageRank |
2194-5357 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao Wang | 1 | 0 | 0.34 |
| Roberta Pappadà | 2 | 17 | 2.44 |
| Fabrizio Durante | 3 | 391 | 59.28 |
| Enrico Foscolo | 4 | 23 | 3.20 |