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yetanotheryacht t1_iqv209k wrote

Derivatives have non-linear outcome on stochastic events. So you can not make linear predictions, only probabilistic guesses

For each derivative you model the probability ranges of their underlying assets changing value. You then take those outcomes to use for setting the expected value of the derivative. The problem is that this all assumes linear probability but the world is defined by big events, not small increments. So when a country invades another country or a pandemic hits, some of the underlying assets will change value in a highly unexpected way, and you probabilistic approach to pricing the derivative is wrong.

Think of derivatives as fire insurance: If you are the one who have sold the derivative you may have to be the one to pay out the insured amount. That is fine if only 1 in 10'000 houses catch fire, under normal conditions, but if 1000 houses are lost due to a wildfire, you have to pay out a lot more than you set aside because your model did not take this big event into account.

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wattnurt t1_iqx04gh wrote

Related, a very influential paper from the early 2000s is partially blamed for the 2008 financial crisis:

https://en.wikipedia.org/wiki/David_X._Li#CDOs_and_Gaussian_copula

It gave "quants" (actuaries) a tool for estimating the inter-dependency between mortgages etc, but they placed undue trust in that formula, and when the housing market collapsed it tore down a lot of things around it with it, even though the formula suggested it shouldn't. It was a classic example of somebody creating a tool, and others picking it up but not really understanding it and then applying it in places where it wasn't reliable.

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