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The Importance of Data Cleaning in Research
With HFT, we like to mark out to pretty short time horizons. The regime of noise or signal to noise in high frequency trading is magnitude higher than most things people study in academia. Filtering outliers is exponentially more important if you don't think about this stuff correctly. On the infrastructure side, I think the biggest lesson we learned sounds kind of silly, but you really need to learn this first hand. You're always going to learn something new.