  We propose a new measure of systemic risk to analyze the impact of the major
financial market turmoils in the stock markets from 2000 to 2023 in the USA,
Europe, Brazil, and Japan. Our Implied Volatility Realized Volatility Systemic
Risk Indicator (IVRVSRI) shows that the reaction of stock markets varies across
different geographical locations and the persistence of the shocks depends on
the historical volatility and long-term average volatility level in a given
market. The methodology applied is based on the logic that the simpler is
always better than the more complex if it leads to the same results. Such an
approach significantly limits model risk and substantially decreases
computational burden. Robustness checks show that IVRVSRI is a precise and
valid measure of the current systemic risk in the stock markets. Moreover, it
can be used for other types of assets and high-frequency data. The forecasting
ability of various SRIs (including CATFIN, CISS, IVRVSRI, SRISK, and Cleveland
FED) with regard to weekly returns of S&P 500 index is evaluated based on the
simple linear, quasi-quantile, and quantile regressions. We show that IVRVSRI
has the strongest predicting power among them.
