Identifying financial crises in real time

► We report an innovative algorithm for detecting a crisis in a time series in real time. ► The algorithm gives robust results for well documented financial crises such as those of 1929 and 1987. ► The method treats stochastic fluctuations by analogy with statistical mechanics formalisms. ► We report unexpected results for financial data from 2011.