  Financial crises are known as crashes that result in a sudden loss of value
of financial assets in large part and they continue to occur from time to time
surprisingly. In order to discover features of the financial network, the
pairwise interaction of stocks has been considered in many research, but the
existence of the strong correlation of stocks and their collective behavior in
crisis made us address higher-order interactions. Hence, in this study, we
investigate financial networks by triplet interaction in the framework of
balance theory. Due to detecting the contribution of higher-order interactions
in understanding the complex behavior of stocks we take the advantage of the
orders parameters of the higher-order interactions. Looking at real data of
financial market obtained from $S\&P500$ through the lens of balance theory for
the quest of network structure in different periods of time near and far from
crisis reveals the existence of a structural difference of the network that
corresponds to different periods of time. Here, we address two well-known
crises the Great regression (2008) and the Covid-19 recession (2020). Results
show an ordered structure forms on-crisis in the financial network while stocks
behave independently far from a crisis. The formation of the ordered structure
of stocks in crisis makes the network resistant against disorder. The
resistance of the ordered structure against applying a disorder (temperature)
can measure the crisis strength and determine the temperature at which the
network transits. There is a critical temperature, $T_{c}$, in the language of
statistical mechanics and mean-field approach which above, the ordered
structure destroys abruptly and a first-order phase transition occurs. The
stronger the crisis, the higher the critical temperature.
