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Home Page: https://arxiv.org/abs/1711.04837
License: MIT License
Deep learning for forecasting company fundamental data
Home Page: https://arxiv.org/abs/1711.04837
License: MIT License
There are 20 features in nips paper, but 56 in the project. How to choose them?
Hi, Thank you for providing this to the community. I was wondering if you could share the code that creates the open-dataset.dat file? I am interested in how the fields are generated/obtained. I have access to an online resource for fundamental data but not sure how to prepare the fields and would like to follow along with the script that createst the open-dataset.dat dataset.
Thanks
Hi I have access to WRDS account but still cannot obtain results close to paper error rate. I am trying to follow approach described in the paper but still getting much higher MSE, can you specify steps to do it?
I saw a simulation part in the experiments folder. Is there a readme text about it? Thank you!
First of all, thanks for sharing this amazing repository. It is a great help for understanding those techniques applied to the finance domain.
I skimmed through the code and I was wondering if there is the possibility to improve the structure of the model and do multiple prediction at the same time. In other words I would be able to test the model on my dataset, outputting the fundamentals at t+1,t+2,t+3 for instance.
To me it looks like the model is able to provide just one single forecast at each timestep, because I don't see such a parameter among the configurations. I am just trying to understand which part of the scripts I should change in order to obtain multiple predictions.
Anyway, thank you again for your great work.
Thank you for making this available,
when i enter: $ python build_data.py --N 10 --exclude_gics 40,45 --filename out.dat --test_mode yes
I get the error "ImportError: No module named configparser"
I have installed configparser and am not sure why I am getting this error
I found that the .dat
file fetched by scripts/build_datfile.py
does not appear to contain all of the necessary columns (saleq_ttm
for example). Unfortunately, I do not have a wrds account.
Would it be possible to provide an example .dat file that contains the needed columns and example values?
Thanks for good job in advance.
I'm blocked on this issue when trying to 'python deep_quant.py'. So, there's a sample or alternative of it for going further?
If I have to construct it myself, with what format should I follow? Looking like benchmark-ew.dat? Thank you.
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