In this index study, the relationships between Stoxx Europe 600 and sector indices are analyzed. This research uses DCoVar and MES as analytical tools developed as a measure of systemic risk and applied to financial institutions, to sectoral subindexes. For the sake of systemic risk assessment we calculate the dynamic correlation model with bivariate t copula distribution. We focus on the impact of sectors on the market. Despite the similarity between the time series plots of both measures, with maximum values on similar days, the compatibility of daily rankings, measured as a percentage of concordant pairs, is equal to about 50%. The rankings of the most and least risky sectors are different and depend on the choice of measure, but in the case of both we observe poor stability. When sectors are ranked in terms of the highest and lowest mean values at specific intervals (designated by the structural break estimation method, which surpisingly detects very similar dates of structural changes) we draw the same conclusions. For both measures we note huge percentage changes in mean values of risk, especially in the period from February 24, 2020 till August 20, 2020 with respect to the previous period. The percentage changes for both intervals indicate the same most risky sectors, but the indications of both measures are not consistent.