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This is the pseudo-intellectual version of your boomer relative ranting about the weatherman on TV, “how does this guy still have a job when he’s always wrong!”

Or the poll-bashing that happened after the 2016 election when an outcome with a 29% chance per one model was observed.

Any interesting forecasting problem is underconstrained. Monte Carlo methods are the classic way to mitigate that one-universe problem.

Nobody can predict the future with certainty. All models are wrong, but some are useful.

by whatever16 hours ago|

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How does Monte Carlo help mitigation?

I fully agree that all models are wrong.

Their main usage is just replaying the past or encoding the modelers assumptions for the future.

But there is no way to know if a model is good or bad.

There would be if we had infinite universes.

by tom_mc4 hours ago|

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Monte Carlo methods are used to estimate the risk associated with a prediction (and presumably an action taken against that prediction). Does that answer your question? I can elaborate if you like.

by whatever13 hours ago|

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It estimates risk based on your current understanding of the universe.

1. No guarantee that the universe tomorrow will behave as the distributions you used in your Monte Carlo today.

2. If the universe stats serving you 10 unlikely events in a row, is your model model wrong, or just 10 unlucky draws? If your model was correct and you start "correcting it" based on these 10 draws, you now made it wrong.

by tom_mc1 hours ago|

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Like the other person said, all models are wrong but some are useful (a quote they did not make up btw). It sounds like you understand how MC works. Do you feel like you've answered your own question regarding how MC helps? I'm trying to be helpful since you asked above.