Anti-correlation network among China A-shares

TL;DR

This paper introduces the first analysis of anti-correlation networks among China A-shares, revealing fundamental topological differences from positive correlation networks and highlighting market asymmetries during rises and declines.

Contribution

It is the first to separately analyze anti-correlation networks in financial systems, providing new insights into their structure and dynamics compared to traditional correlation studies.

Findings

Anti-correlation networks differ significantly from positive correlation networks in topology.

Market declines and rises exhibit asymmetric effects in anti-correlation networks.

The methodology offers new perspectives for risk management and portfolio analysis.

Abstract

The correlation-based financial networks are studied intensively. However, previous studies ignored the importance of the anti-correlation. This paper is the first to consider the anti-correlation and positive correlation separately, and accordingly construct the weighted temporal anti-correlation and positive correlation networks among stocks listed in the Shanghai and Shenzhen stock exchanges. For both types of networks during the first 24 years of this century, fundamental topological measurements are analyzed systematically. This paper unveils some essential differences in these topological measurements between the anti-correlation and positive correlation networks. It also observes an asymmetry effect between the stock market decline and rise. The methodology proposed in this paper has the potential to reveal significant differences in the topological structure and dynamics of a complex financial system, stock behavior, investment portfolios, and risk management, offering insights that are not visible when all correlations are considered together. More importantly, this paper proposes a new direction for studying complex systems: the anti-correlation network. It is well worth reexamining previous relevant studies using this new methodology.