Comparison of empirical and shrinkage correlation algorithm for clustering methods in the futures market

Andrea Di Iura ()
Additional contact information
Andrea Di Iura: Enel SpA

SN Business & Economics, 2022, vol. 2, issue 8, 1-17

Abstract: Abstract The correlation structure of the futures market obtained using daily data from 2009 to 2020 has been investigated to show how different sectors, such as energy or agriculture, produce a hierarchical clustering. The structure depends on the estimation of the correlation matrix; two techniques have been considered: the empirical and the shrinkage one. The networks obtained from those matrices differ from the presence of a hub, the UK Feed Wheat future, that drives the whole market if the shrinkage estimator for the correlation matrix is used. Additionally, an analysis of hierarchical structure changes in time adopting a measure of the similarity among clusters has been considered. It has been observed that the Ward criterion and the shrinkage estimation are the most robust to forecast the network structure.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s43546-022-00265-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:snbeco:v:2:y:2022:i:8:d:10.1007_s43546-022-00265-8

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/43546

DOI: 10.1007/s43546-022-00265-8

Access Statistics for this article

SN Business & Economics is currently edited by Gino D'Oca

More articles in SN Business & Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().