Systemic Illiquidity Noise-Based Measure—A Solution for Systemic Liquidity Monitoring in Frontier and Emerging Markets

The paper presents an alternative approach to measuring systemic illiquidity applicable countries with frontier and emerging financial markets, where other existing methods are not applicable. We develop a novel Systemic Illiquidity Noise (SIN)-based measure, using the Nelson–Siegel–Svensson methodology in which we utilize curve-fitting error as indicator of system illiquidity. empirically apply our method set 10 divergent Central Eastern Europe countries—Bulgaria, Croatia, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia—in period 2006–2020. results show three periods increased risk sample period: global crisis, European public debt COVID-19 pandemic. They also allow us identify sets different liquidity characteristics. analysis illustrates impact introduction euro on risk. proposed may be consequence for regulators macroprudential bodies: it allows contemporaneous monitoring discussed at minimal cost well-known models easily accessible data.