The focus of this study to measure the varying irreversibility of stock markets. A fundamental idea of this study is that financial systems are complex and nonlinear systems that are presented to be non-Gaussian fractal and chaotic. Their complexity and different aspects of nonlinear properties, such as time ir- reversibility, vary over time and for a long-range of scales. Therefore, our work combines econometrical and econophysical approaches to measure the com- plexity and irreversibility of the time series. Econometrical approaches include Guzik’s index, Porta’s index, Costa’s index, and based on complex networks measures. Multiscale time irreversibility index and based on entropy measures approaches are taken as econophysical. Our study presents that the correspond- ing measures can be used as indicators or indicator-precursors of crisis states in stock markets.