A portfolio diversification strategy via tail dependence clustering

Hao Wang; Roberta Pappadà; Fabrizio Durante; Enrico Foscolo

doi:10.1007/978-3-319-42972-4_63

Back

A portfolio diversification strategy via tail dependence clustering

Book chapter

Peer reviewed

A portfolio diversification strategy via tail dependence clustering

Hao Wang, Roberta Pappadà, Fabrizio Durante and Enrico Foscolo

Soft Methods for Data Science, Vol.456, pp.511-518

Advances in Intelligent Systems and Computing, 456, Springer

2017

DOI: https://doi.org/10.1007/978-3-319-42972-4_63

Handle:

https://hdl.handle.net/10863/3016

Abstract

Quantitative methods and economic modeling

Financial markets

Computational statistics

Portfolio optimization

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.

Files and links (1)

url

http://link.springer.com/chapter/10.1007/978-3-319-42972-4_63View

Details

Title: A portfolio diversification strategy via tail dependence clustering
Creators: Hao Wang
Roberta Pappadà
Fabrizio Durante
Enrico Foscolo
Publication Details: Soft Methods for Data Science, Vol.456, pp.511-518
Editor(s): Vantaggi B, Ferraro MB, Giordani P, Gil MA, Gagolewski M, Grzegorzewski P, Hryniewicz O
ISBN: 978-3-319-42971-7
EISBN: 978-3-319-42972-4
ISSN: 2194-5357
EISSN: 2194-5365
Series / Volume: Advances in Intelligent Systems and Computing
456
Publisher: Springer
Cham
Format: Print
Number of pages: 8
Identifiers: 978-3-319-42971-7
(UNIBZ)21168194
991005773436501241
Web of Science ID: 000390837600063
Scopus ID: 2-s2.0-84988391773
Academic Unit: Faculty of Economics and Management
Faculty of Economics and Management
Language: English
Resource Type: Book chapter
Author Names String: Wang H, Pappadà R, Durante F, Foscolo E
Additional Description: srcEditors: Vantaggi B, Ferraro MB, Giordani P, Gil MA, Gagolewski M, Grzegorzewski P, Hryniewicz O
Projected: 3931
unibz-area: Quantitative methods and economic modeling
ERC: Statistics;Financial markets, asset prices, international finance
ERCCODE: PE1_14;SH1_5
MIURSSD: Statistica;Statistica economica
MIURSSDCODE: SECS-S/01;SECS-S/03

Metrics

50 Record Views