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Some highly recommended books
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Some highly recommended books

  #471 (permalink)
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Not exactly trading related but this was a one sitting book for me. Really loved everything about it. The title pretty much says it all.

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Reminds me of this cartoon I found on a blog
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"identify your limitations and then ignore them"

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  #472 (permalink)
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centaurer View Post
Not exactly trading related but this was a one sitting book for me. Really loved everything about it. The title pretty much says it all.

Thanks for sharing the book and cartoon. I will have to add that to my summer reading list. I just showed the cartoon to my 10 year-old son, because he struggles with this.

~vmodus

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  #473 (permalink)
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Marcus López de Prado: Advances in Financial Machine Learning

Requires advanced knowledge of mathematics, not easy to read, but worth the effort.

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  #474 (permalink)
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Fat Tails View Post
Marcus López de Prado: Advances in Financial Machine Learning

Requires advanced knowledge of mathematics, not easy to read, but worth the effort.

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Google books has an audio book of it too for like 20 bucks that is so worth it.

I have taken a step back and need to get my econometric and proper time series analysis chops up to speed.

Marcos is my guru now for sure. Hoping to make some new dissssccccoveries and find some new sssssignals.

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  #475 (permalink)
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centaurer View Post
Google books has an audio book of it too for like 20 bucks that is so worth it.

I have taken a step back and need to get my econometric and proper time series analysis chops up to speed.

Marcos is my guru now for sure. Hoping to make some new dissssccccoveries and find some new sssssignals.


Thank you for your comment.

But how would you understand mathematical equations when listening to an audio book?

This is not a detective novel. It is a difficult read, and you won't understand it when simply listening.

And without the mathematics it is just a waste of time.

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  #476 (permalink)
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Fat Tails View Post
Thank you for your comment.

But how would you understand mathematical equations when listening to an audio book?

This is not a detective novel. It is a difficult read, and you won't understand it when simply listening.

And without the mathematics it is just a waste of time.

It isn't a calculus text book though either. I would say Marcos did a great job of explaining the concepts in english with as little math as possible and then python code for practical use.

I listen to it in the car. I have had my mind blown so many times listening and I haven't even got past part 2. I also don't mean not to get the text itself and just listen to it. Really, the audio book might be the best purchase I have ever made because instead of listening to nonsense sports talk radio to and from work I get intense trading knowledge and then go back to the text and try to put it all together.

It is such a dense book of trading knowledge.

I would also say the fact the publisher bothered putting in resources to produce an audio book of a quant machine learning text speaks to the clarity of De Prado's thought.


Last edited by centaurer; May 10th, 2019 at 05:20 PM.
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  #477 (permalink)
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Fat Tails View Post
Marcus López de Prado: Advances in Financial Machine Learning

Requires advanced knowledge of mathematics, not easy to read, but worth the effort.

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What sort of mathematics / stats subjects do I need to learn before reading this book? I've got the book but struggle to comprehend the math equations and some of the mathy text. Any books or online courses you can recommend ? Thanks!

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  #478 (permalink)
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quantstyle View Post
What sort of mathematics / stats subjects do I need to learn before reading this book? I've got the book but struggle to comprehend the math equations and some of the mathy text. Any books or online courses you can recommend ? Thanks!

IMO part of the hurdle is Marcos econometrics background. The machine learning stuff you can learn on fast.ai.
I think the Fractionally Differentiated Features chapter is a good example. If you don't know the time series analysis language he is talking in I don't know how the math can really be put into context anyway. Analysis of Financial Time Series by Tsay is a standard text in that area for finance.
Fractionally Differentiated Features chapter is all about how standard econometric transforms to make a time series stationary wipes out too much memory from the time series and then he shows you how to not do that with python code.

If you don't know why you would want to make a time series stationary in the first place you need to read something like Tsay. I also got Using Econometrics A Practical Guide 7th Edition as it is much less heavy than Tsay. Tsay is cool though because there is a R package with all the data used in the book. I also got A Primer for Unit Root Testing by K Patterson

In general the format is he explains the concept in English with equations and then there is the python implementation. If you are unsure of a part of the equation you should be able to get an idea from the python code.

Don't forget people use and understand moving averages all the time without knowing anything about this equation
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The concept is what is important. Not the math.
I would also highly recommend reading A Mathematician’s Lament
https://www.maa.org/external_archive/devlin/LockhartsLament.pdf

Our attitude towards math is disgraceful.

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  #479 (permalink)
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centaurer View Post
IMO part of the hurdle is Marcos econometrics background. The machine learning stuff you can learn on fast.ai.
I think the Fractionally Differentiated Features chapter is a good example. If you don't know the time series analysis language he is talking in I don't know how the math can really be put into context anyway. Analysis of Financial Time Series by Tsay is a standard text in that area for finance.
Fractionally Differentiated Features chapter is all about how standard econometric transforms to make a time series stationary wipes out too much memory from the time series and then he shows you how to not do that with python code.

If you don't know why you would want to make a time series stationary in the first place you need to read something like Tsay. I also got Using Econometrics A Practical Guide 7th Edition as it is much less heavy than Tsay. Tsay is cool though because there is a R package with all the data used in the book. I also got A Primer for Unit Root Testing by K Patterson

In general the format is he explains the concept in English with equations and then there is the python implementation. If you are unsure of a part of the equation you should be able to get an idea from the python code.

Don't forget people use and understand moving averages all the time without knowing anything about this equation
Please register on futures.io to view futures trading content such as post attachment(s), image(s), and screenshot(s).


The concept is what is important. Not the math.
I would also highly recommend reading A Mathematician’s Lament
https://www.maa.org/external_archive/devlin/LockhartsLament.pdf

Our attitude towards math is disgraceful.

Thank you very much for taking so much time to write out this comprehensive reply! It has been very useful to me.


I have heard of fast.ai but wasn't sure it would be useful for finance-related machine learning as it seemed to be more focused on CNN's / computer vision. Will definitely take a look at it again after your recommendation!

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