This story was originally published on HackerNoon at: https://hackernoon.com/why-ml-can-predict-the-weather-but-not-financial-markets.
Why machine learning models fail in finance: noisy data, scarce samples, and chaotic markets make prediction nearly impossible.
Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories.
You can also check exclusive content about #ai-in-finance, #ai-trading, #financial-markets, #trading-algorithms, #market-prediction-ai, #financial-data-noise, #synthetic-financial-data, #hackernoon-top-story, and more.


This story was written by: @hacker47950068. Learn more about this writer by checking @hacker47950068's about page,
and for more stories, please visit hackernoon.com.



Financial data is just harder to work with than data in other domains, mainly for three reasons: Too much noise, not enough data, and constantly changing markets. Grigory Heron: The problem is that they only work in isolation. Nobody has managed to put them all into a single trading machine.

Ver todos los episodios