What Is (Fat) Tail Risk?

The Bank of America Merrill Lynch #investors survey indicates that #inflation is currently the biggest tail #risk concern for professional investors. But what do we actually mean by tail risk? As investors we worry about extreme negative events/returns, but embrace extreme positive events/returns. With tail risk, we are technically talking about negative three standard deviation or worse events. In a normal distribution these events happen about 0.13% of the time. In terms of daily returns, these are the extreme negative events that happen about once every three years. Unfortunately, #asset #returns are not normally distributed. They are negatively skewed and exhibit positive excess kurtosis. Negative events occur more often than positive events and both the tails are fat. Fat tail risk still measures extreme negative #events. They just happen to occur more often than a normal distribution would suggest. #financialmarkets #cfainstitute #caia #frm
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[@aertybhujm1]

simple but informative video
Big thanks from Taiwan

[@staxx8788]

Love this explanation. I came across your channel today! Thank you for your consistency and I hope to learn more from you

[@anand6781]

Thanks for this!

[@KMLogKM]

Thanks for indepth exlaination

[@filiper.5479]

Thanks for that

[@claudiaschneider3980]

Thank you great video😊

[@anthonylovesmary]

Just read black swan - if I’m not mistaken, seems you have this exactly wrong. Taleb’s point is the fat tail events happen LESS frequently, but their impact is has excessive impact on overall distribution characteristic. What am I missing here?

[@investmentmanagementlab4528]

By definition, distributions with fat tails are those in which extreme events occur more often than they do in normal distributions. Compared to fat-tailed distributions, in the normal distribution events that deviate from the mean by five or more standard deviations have lower probability, meaning that in the normal distribution extreme events are less likely than for fat-tailed distributions. Stock market returns have fat tails. This means that extreme negative returns in the stock market occur more often than they would if stock market returns were normally distributed.

[@frenchmarty7446]

In a fat tailed distribution, a smaller portion of events determine the majority of the properties.
It is not so much an issue of frequency but importance. A smaller and smaller number of events determine the overall properties of the distribution. Hence "black swan" events because you don't have a large enough sample size to know the underlying properties of the system.
If, by fat-tailed event, you mean +/- >3 standard deviations, then you are completely wrong. They occur orders of magnitude more frequently in a fat tailed distribution than in a gausaian/normal distribution.