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Quant firms use Kalman filters to solve all sorts of problems, because they elegantly solve the problem of optimally estimating the state of a dynamic system from noisy measurements. You kind of use Kalman filters every time you drive in rain, snow, or low visibility — you assign trust-weights to what you see with your eyes, what your GPS tells you, and your memory of the road, depending on how trustworthy or noisy they feel at each moment. That’s such a good analogy, actually, I’m using that ne
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