Addressing the need for risk measures in various markets, the Financial Risk Meter (FRM) effectively predicts future market risks. The FRM uses Quantile-LASSO regression to identify systemic financial risks and dependencies among extreme events across different assets. It connects asset pricing kernel volatility, the highest possible Sharpe ratio, and overall market volatility. In this study, FRM@China demonstrates its strength in detecting systemic risks and shows a negative correlation with the interconnectedness of financial institutions during extreme events. When applied to major financial institutions in Emerging Markets, the FRM highlights peak risks during crises. The expectile FRM improves the prediction of extreme losses and offers a range of risk indicators. Overall, the FRM provides valuable insights into systemic risks across various markets, helping policymakers and investors make informed decisions.