Asset trees and asset graphs in financial markets

TL;DR

This paper proposes a new method for constructing dynamic asset graphs in financial markets, which are more flexible than asset trees and exhibit different structural and stability properties over time.

Contribution

The paper introduces a novel methodology for creating asset graphs that are not constrained to be trees, allowing for more accurate representation of asset correlations.

Findings

Asset graphs decay more slowly than asset trees initially.

Asset trees are more fragile structurally than asset graphs.

Asset graph degree distributions are less clearly scale-free than asset trees.

Abstract

This paper introduces a new methodology for constructing a network of companies called a dynamic asset graph. This is similar to the dynamic asset tree studied recently, as both are based on correlations between asset returns. However, the new modified methodology does not, in general, lead to a tree but a graph, or several graphs that need not be inter-connected. The asset tree, due to the minimum spanning tree criterion, is forced to ``accept'' edge lengths that are far less optimal (longer) than the asset graph, thus resulting in higher overall length for the tree. The same criterion also causes asset trees to be more fragile in structure when measured by the single-step survival ratio. Over longer time periods, in the beginning the asset graph decays more slowly than the asset tree, but in the long-run the situation is reversed. The vertex degree distributions indicate that the possible scale free behavior of the asset graph is not as evident as it is in the case of the asset tree.