This paper proposes an empirical methodology to measure systemic risk by quantifying the expected capital shortage of financial institutions in a future crisis. The authors introduce a Systemic Risk Index (SRISK) that combines a firm's leverage and Marginal Expected Shortfall (MES), which represents the expected equity loss if the market declines significantly. The MES is estimated using a dynamic model that captures time-varying volatility and correlation, with flexible inference methods allowing for potential tail dependence. The model is applied to a sample of top US financial firms, revealing that the methodology provides useful rankings of systemically risky firms at various stages of the financial crisis. The results highlight the deterioration of the financial system's capitalization starting from January 2007 and show that as of July 2010, the financial system has not fully recovered. The paper also discusses the limitations and extensions of the proposed methodology, including the use of different volatility and correlation specifications and the evaluation of forecast accuracy.This paper proposes an empirical methodology to measure systemic risk by quantifying the expected capital shortage of financial institutions in a future crisis. The authors introduce a Systemic Risk Index (SRISK) that combines a firm's leverage and Marginal Expected Shortfall (MES), which represents the expected equity loss if the market declines significantly. The MES is estimated using a dynamic model that captures time-varying volatility and correlation, with flexible inference methods allowing for potential tail dependence. The model is applied to a sample of top US financial firms, revealing that the methodology provides useful rankings of systemically risky firms at various stages of the financial crisis. The results highlight the deterioration of the financial system's capitalization starting from January 2007 and show that as of July 2010, the financial system has not fully recovered. The paper also discusses the limitations and extensions of the proposed methodology, including the use of different volatility and correlation specifications and the evaluation of forecast accuracy.