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My honest opinion is that any ML related to finance that you learn outside of an investment firm is mostly a waste of time. The amount of data and nuance that s

My honest opinion is that any ML related to finance that you learn outside of an investment firm is mostly a waste of time. The amount of data and nuance that successful models encompass is staggering. Unless you do something like scrape WSB and predict the next MEME stock, ML for finance makes no sense. You need credit card data, 10ks, tick data, economic forecasts, interest rates, fed moves, etc. You can carve out a niche, but if you do, forget about finding something on the internet that will tell you how to do that.

canaryyellow 5y ago
Are u saying that finance books dont really help ?
- andyxor 5y ago
  finance book do help, 'ML for finance' books rarely do, the domain is too new and attracts many charlatans. You're better off just learning ML from its classics like Hastie & Tibshirani , Tom Mitchell, or Bishop PRML. And learn finance from its own classics you can find in any "financial engineering" curriculum. There is one I liked though because of hands-on approach: "Machine Learning for Algorithmic Trading" https://www.amazon.com/Machine-Learning-Algorithmic-Trading-alternative-dp-1839217715/dp/1839217715/ref=dp_ob_title_bk https://www.amazon.com/Machine-Learning-Algorithmic-Trading-... just assume its listed "strategies" are a sort of primitive "hello world"
  - dhruva_k 5y ago
    I think you have to read these books with the knowledge that the strategies you find in them are not going to be the ones to make you millions. No one ever got rich reading a book and copying exactly what it told them to, otherwise we'd all have our yachts in Miami. I personally have no issue with ML for finance books as long as they aren't just explaining rigid strategies, but more how to approach the topic of forecasting something as difficult as the financial markets. I think it's more about learning how to think when you're looking at these charts vs what is the one ML model that is going to bring me success for the rest of my life.
sooheon 5y ago
There are many games at different abstraction levels in finance, and I agree to find an edge at the level you're describing is exceedingly difficult. That said, Fama and French won a Nobel Prize with data stewardship and regressions. There's definitely a place for understanding basic financial data and ML concepts even for the retail investor.

canaryyellow 5y ago

Are u saying that finance books dont really help ?

andyxor 5y ago
finance book do help, 'ML for finance' books rarely do, the domain is too new and attracts many charlatans. You're better off just learning ML from its classics like Hastie & Tibshirani , Tom Mitchell, or Bishop PRML. And learn finance from its own classics you can find in any "financial engineering" curriculum. There is one I liked though because of hands-on approach: "Machine Learning for Algorithmic Trading" https://www.amazon.com/Machine-Learning-Algorithmic-Trading-alternative-dp-1839217715/dp/1839217715/ref=dp_ob_title_bk https://www.amazon.com/Machine-Learning-Algorithmic-Trading-... just assume its listed "strategies" are a sort of primitive "hello world"
- dhruva_k 5y ago
  I think you have to read these books with the knowledge that the strategies you find in them are not going to be the ones to make you millions. No one ever got rich reading a book and copying exactly what it told them to, otherwise we'd all have our yachts in Miami. I personally have no issue with ML for finance books as long as they aren't just explaining rigid strategies, but more how to approach the topic of forecasting something as difficult as the financial markets. I think it's more about learning how to think when you're looking at these charts vs what is the one ML model that is going to bring me success for the rest of my life.

sooheon 5y ago

There are many games at different abstraction levels in finance, and I agree to find an edge at the level you're describing is exceedingly difficult. That said, Fama and French won a Nobel Prize with data stewardship and regressions. There's definitely a place for understanding basic financial data and ML concepts even for the retail investor.