Loss of structural balance in stock markets

TL;DR

This paper investigates how the structural balance of stock market networks changes over time and how these changes impact stock predictability, revealing a transition linked to market shocks and sector reorganization.

Contribution

It introduces a novel analysis of network balance in stock markets using rank correlations and links these structural changes to predictability and market events.

Findings

Balance-unbalance transition after 2011 US market shock

Reorganization of low-cap stocks in non-financial sector

Decrease in stock predictability associated with network imbalance

Abstract

We use rank correlations as distance functions to establish the interconnectivity between stock returns, building weighted signed networks for the stocks of seven European countries, the US and Japan. We establish the theoretical relationship between the level of balance in a network and stock predictability, studying its evolution from 2005 to the third quarter of 2020. We find a clear balance-unbalance transition for six of the nine countries, following the August 2011 Black Monday in the US, when the Economic Policy Uncertainty index for this country reached its highest monthly level before the COVID-19 crisis. This sudden loss of balance is mainly caused by a reorganization of the market networks triggered by a group of low capitalization stocks belonging to the non-financial sector. After the transition, the stocks of companies in these groups become all negatively correlated between them and with most of the rest of the stocks in the market. The implied change in the network topology is directly related to a decrease in stocks predictability, a finding with novel important implications for asset allocation and portfolio hedging strategies.