Sehr sehr sehr gutes Interview mit einer Janestreet flow tratderin/researcherin.
Auszug:
"Yeah, I guess we can just go back to your original question of how is machine learning different in a financial context versus in other settings? And I dunno what to tell you, but machine learning in a financial context is just really, really hard. A lot of the things that you might learn in school or in papers or something, they just don’t work. And why doesn’t that work? I think ultimately it boils down to a few pathologies or quirks of financial data. I guess one mental model that I have that I’m borrowing from a coworker that I really liked is you can think of machine learning in finance is similar to building an LLM or text modeling except that instead of having, let’s say one unit of data, you have 100 units of data. That sounds great. However, you have one unit of useful data and 99 units of garbage and you do not know what the useful data is and you do not know what the garbage or noise is. And you need to basically be able to extract a signal in this extremely high noise regime with techniques that were designed for much higher signal to the noise ratio application domains."
https://signalsandthreads.com/finding-si...the-noise/
Auszug:
"Yeah, I guess we can just go back to your original question of how is machine learning different in a financial context versus in other settings? And I dunno what to tell you, but machine learning in a financial context is just really, really hard. A lot of the things that you might learn in school or in papers or something, they just don’t work. And why doesn’t that work? I think ultimately it boils down to a few pathologies or quirks of financial data. I guess one mental model that I have that I’m borrowing from a coworker that I really liked is you can think of machine learning in finance is similar to building an LLM or text modeling except that instead of having, let’s say one unit of data, you have 100 units of data. That sounds great. However, you have one unit of useful data and 99 units of garbage and you do not know what the useful data is and you do not know what the garbage or noise is. And you need to basically be able to extract a signal in this extremely high noise regime with techniques that were designed for much higher signal to the noise ratio application domains."
https://signalsandthreads.com/finding-si...the-noise/
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