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In statistics, the “tails” of the return distribution are extreme outcomes at either end of the bell curve \u2013 events that are rare, but when they do occur, are far larger in magnitude than the everyday volatility (“standard deviation”). Tail risk specifically refers to the left tail: severe risk negative<\/em> Return. Standard portfolio models often assume that asset returns follow a normal distribution. In practice, financial markets exhibit what statisticians call “fat tails” \u2013 meaning extreme events (some of them known as “black swans”). More often, with more seriousness<\/strong>compared to model predictions. The 2008 global financial crisis (GFC), the 2020 COVID-19 crash, and the dot-com collapse of 2000\u20132002 were all, in theory, statistical outliers. In practice, each of them has occurred in the same working lifetime. In the Asian context, an example of a statistical externality is the 1997…<\/div>\n