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superposition


Total Posts: 2
Joined: Dec 2016
 
Posted: 2016-12-30 07:39
Has anyone tried to use swig to build QuantLib for Python. I want to be able to use TensorFlow, quandl, and QuantLib all at the same time.


katastrofa


Total Posts: 448
Joined: Jul 2008
 
Posted: 2016-12-30 10:09
What for?

mtsm


Total Posts: 216
Joined: Dec 2010
 
Posted: 2016-12-30 15:01
How about so she can "try logistic regression first" on quandl data piped through quantlib analytics?

katastrofa


Total Posts: 448
Joined: Jul 2008
 
Posted: 2016-12-30 15:28
? I asked a serious question. If you want to play with algotrading stuff, you don't need QuantLib.

mtsm


Total Posts: 216
Joined: Dec 2010
 
Posted: 2016-12-30 16:19
I made a serious comment.

How do you know she wants to play with algotrading stuff and even if, I can see a lot of reasons you would want to use a quant analytics library.

What's your preferred asset class katastrofa?

katastrofa


Total Posts: 448
Joined: Jul 2008
 
Posted: 2016-12-30 17:38
Cockle shells.

superposition


Total Posts: 2
Joined: Dec 2016
 
Posted: 2016-12-31 03:50
My bad. I should just use scipy and panda.


katastrofa


Total Posts: 448
Joined: Jul 2008
 
Posted: 2016-12-31 19:16
That's a good start. Also sk-learn can be useful. Don't get bogged down in mastering complex frameworks. It will distract you.

phy


Total Posts: 18
Joined: Nov 2013
 
Posted: 2018-03-01 04:00
There are R Wrappers for Quantlib (https://cran.r-project.org/web/packages/RQuantLib/index.html) and Tensorflow (https://tensorflow.rstudio.com/). Quandl API as well.

finanzmaster


Total Posts: 157
Joined: Feb 2011
 
Posted: 2018-04-14 10:41
Here is a use case and instruction how to build Python-QuantLib from source
QuantLib Python – Twisting a Snake to fit a Yieldcurve

Unfortunately Python-QuantLib does not provide the whole functionality of the QuantLib (well, one have sources and can (let) implement the missing features).
Anyway, I find it is much better than e.g. QuantLibXL

www.yetanotherquant.com - Knowledge rather than Hope: A Book for Retail Investors and Mathematical Finance Students
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