  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.
