Tandon in the News

How Is Machine Learning Different In Finance Than Other Fields?


Answer by Igor Halperin, Research Professor of Financial Machine Learning at NYU [Tandon School of Engineering], on Quora: “In my view, the main differences stem from differences in data. In finance, data are (very) noisy, and often non-stationary. “Signals” cannot be split from “noise” in any unique way, as a matter of principle. This is very different from, say, image processing, where the level of noise can be controlled, at least in principle. Also, the notion of non-stationary data is non-existent for image processing. Because of a pronounced role of noise, some ML models, for example non-probabilistic models, are not very useful in finance.”

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