Towards the financial crisis of 2007 to 2008, speculative bubbles prevailed in various financial assets. Whether these bubbles are an economy-wide phenomenon or market specific events is an important question. This study develops a testing approach to investigate whether the bubbles lie in the common or in the idiosyncratic components of large-dimensional financial panel data sets. To this end, we extend the right-tailed unit root tests to common factor models, benchmarking the panel analysis of nonstationarity in idiosyncratic and common component (PANIC) proposed by Bai and Ng (2004). We find that when the PANIC test is applied to the explosive alternative hypothesis as opposed to the stationary alternative hypothesis, the test for the idiosyncratic component may suffer from the nonmonotonic power problem. In this paper, we newly propose a cross-sectional (CS) approach to disentangle the common and the idiosyncratic components in a relatively short explosive window. This method first estimates the factor loadings in the training sample and then uses them in cross-sectional regressions to extract the common factors in the explosive window. A Monte Carlo simulation shows that the CS approach is robust to the nonmonotonic power problem. We apply this method to 24 exchange rates against the U.S. dollar to identify the currency values that were explosive during the financial crisis period.