Live data from Hacker News

Introduction to Machine Learning for Finance

algofin.substack.com

11–20 of 34 posts

Re: Introduction to Machine Learning for Finance

#11
post #4

Anyone have any good books I can read to learn a bit more about this sort of application? I really like the finance stuff, feels like a natural marriage with DS and ML. I don't know nearly enough to expand on what I mean.

Advances in Financial Machine Learning by Marcos Lopez de Prado is one of the best books i read last year. Especially on back testing, strategy risk are my fav.

way overrated imo, you will learn neither finance nor ML from this book, don't spend your money on this.

Given author's tendency for excessive self-promotion I would take any of his advice with a grain of a salt.

Besides he seems to have lost a ton of money for AQR, given his short tenure there. People who make money rarely publish.

if someone is really interested in finance and ML learn each on its own, in finance start with Hull Derivatives, in ML may be some coursera course.

Also quantstart blog has excellent tutorials and 'getting started' guides.

Re: Introduction to Machine Learning for Finance

#12
post #11

Earlier quoted context omitted.

Advances in Financial Machine Learning by Marcos Lopez de Prado is one of the best books i read last year. Especially on back testing, strategy risk are my fav.

way overrated imo, you will learn neither finance nor ML from this book, don't spend your money on this. Given author's tendency for excessive self-promotion I would take any of his advice with a grain of a salt. Besides he seems to have lost a ton of money for AQR, given his short tenure there. People who make money rarely publish. if someone is really interested in finance and ML learn each on its own, in finance s…

Agreed. why does this get rated by everyone on the internet? I read it, and it's total amateur hour.

Just the code examples are bewildering and atrocious.

Still looking for an alternastive.

Re: Introduction to Machine Learning for Finance

#13
post #11

Earlier quoted context omitted.

Advances in Financial Machine Learning by Marcos Lopez de Prado is one of the best books i read last year. Especially on back testing, strategy risk are my fav.

way overrated imo, you will learn neither finance nor ML from this book, don't spend your money on this. Given author's tendency for excessive self-promotion I would take any of his advice with a grain of a salt. Besides he seems to have lost a ton of money for AQR, given his short tenure there. People who make money rarely publish. if someone is really interested in finance and ML learn each on its own, in finance s…

[deleted]

Re: Introduction to Machine Learning for Finance

#15
post #11

Earlier quoted context omitted.

Advances in Financial Machine Learning by Marcos Lopez de Prado is one of the best books i read last year. Especially on back testing, strategy risk are my fav.

way overrated imo, you will learn neither finance nor ML from this book, don't spend your money on this. Given author's tendency for excessive self-promotion I would take any of his advice with a grain of a salt. Besides he seems to have lost a ton of money for AQR, given his short tenure there. People who make money rarely publish. if someone is really interested in finance and ML learn each on its own, in finance s…

Working in the field (HFT market maker) and agree with this assessment. The book is pretty useless in practice - it's basically a vehicle of self promotion for his academic career.

Re: Introduction to Machine Learning for Finance

#16
post #3
post #2

What are the great successes of machine learning in finance?

Great question! Does Renaissance Technologies count as ML? I honestly don't know where the line between quantitative/algorithmic and ML is - I suspect it's blurry.

Is there any proof of Renaissance not being just insider trading or a Ponzi scheme?

Re: Introduction to Machine Learning for Finance

#17
post #11

Earlier quoted context omitted.

way overrated imo, you will learn neither finance nor ML from this book, don't spend your money on this. Given author's tendency for excessive self-promotion I would take any of his advice with a grain of a salt. Besides he seems to have lost a ton of money for AQR, given his short tenure there. People who make money rarely publish. if someone is really interested in finance and ML learn each on its own, in finance s…

Working in the field (HFT market maker) and agree with this assessment. The book is pretty useless in practice - it's basically a vehicle of self promotion for his academic career.

What books would u recommend from ur experience? That aren't self promotion

Re: Introduction to Machine Learning for Finance

#18

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…

Are u saying that finance books dont really help ?

Re: Introduction to Machine Learning for Finance

#19

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…

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.

Re: Introduction to Machine Learning for Finance

#20

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…

Are u saying that finance books dont really help ?

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-...

just assume its listed "strategies" are a sort of primitive "hello world"

Post reply on HN