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07121941

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.

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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.

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

"Trading and Exchanges: Market Microstructure for Practitioners" is a good introductory book that covers how markets work on a high level. It doesn't teach you how to build profitable systems. That you won't find anywhere anyway.

Link for the lazy of a Draft Copy available made in 2002:

http://www.acsu.buffalo.edu/~keechung/MGF743/Readings/Tradin...

Also a weird book-like slide set that explains what the book is about (and the very important concepts/market participants):

https://rkbookreviews.files.wordpress.com/2013/12/trading-an...

This book is great for complete non practitioners. It was such a great read in 2015 when I graduated and went to work at a large broker-dealer.

Thanks for the recommendations. Since, I dont work on the field as closely and mostly on a observatory capacity. Ill take a look at the recommendations.

>it's basically a vehicle of self promotion for his academic career

i would say that a full ~25% of technical books are this - solely for the purposes of building brand rather than communicating effectively.

Worked in the field, read the book. Strongly agree that the book is essentially useless. Hull is a good starting point.

Not strictly ML, but "Optimization Methods in Finance" by Cornuejols et al [1] a great reference. It introduces optimization algorithms and modeling technique as well as finance applications in alternating chapters.

[1] https://doi.org/10.1017/9781107297340

Read "Beat the market: A scientific stock market system" by Edward Thorp

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