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Code for IJCAI 2021 main conference paper "Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling"

Python 100.00%

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question regarding missing data in prediction phase

Hi!

Appreciate for sharing such greate work!

My concern regarding to the pratical usability of this whole pipeline is: if you select a stock universe i.e., stocks in the CSI300 index, or just simply select n stocks (doesn't really matter), to train the model, then how is the model gonna functioning well (do the right prediction) if some stocks quit the market, or stopped trading for a short period? From my understanding the vertices and edges cannot be missing, or nan?

Historical stock data missing

Dear authors,

Thanks for your great work!

I am trying to run this model, but I find that there is a lack of historical stock data. And the folder 'data' mentioned in 'config_classification.yaml' is missing. Could you please provide the relevant data and files?

Thank you!

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