Topic · Statistics & Econometrics
← All topicsSimulation Methods
15 articles · 2 checkpoints · 9 deeper reads · 4 reference notes
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A Monte Carlo estimate is itself a random number with its own margin of error, and that error shrinks only with the square root of how many paths you run, so an extra decimal place of precision is far more expensive than it looks.
The ordinary bootstrap re-draws from your one sample to estimate how uncertain a statistic is, a trick that quietly breaks for dependent data, heavy tails, and the extreme quantiles quants care about most.
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