Codependence and Dissimilarity Measures

Dany Cajas
Additional contact information
Dany Cajas: Orenji EIRL

Chapter Chapter 6 in Advanced Portfolio Optimization, 2025, pp 89-110 from Springer

Abstract: Abstract This chapter explains how to calculate several kinds of measures that allow readers to quantify linear, nonlinear, and tail dependence relationships among assets. These measures are mainly used as inputs of machine learning asset allocation algorithms to create classifications of assets based on agglomerative hierarchical clustering algorithms and to build constraints based on the graphical representation of assets relationships.

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-84304-4_6

Ordering information: This item can be ordered from
http://www.springer.com/9783031843044

DOI: 10.1007/978-3-031-84304-4_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().