<p>The short answer is no.</p>
<p>Time series models model a single time series. If you want to model N time series you need N time series models. XGBoost is no different when used for time series modeling. The only exception to this would be deep learning using transfer learning but that is a different animal.</p>

CC BY-SA 4.0
2022-11-10T13:01:27.097Z
2022-11-10T13:01:27.097Z
Brian O'Donnell
<p>I built an xgboost model to predict stock it now trains on 1 stock at a time its a csv file I use pandas to load it.
Is there a way to train the model on multiple stocks at the same time? What would be the best approach?
I don't need code just guidance as all my research has failed</p>

<time-series><gradient-boosting><boosting>
Can i train xgboost on multiple time series csv files at the same time?
AJB
# Can i train xgboost on multiple time series csv files at the same time?

(Asked by: username_0 on 2022-11-08)

I built an xgboost model to predict stock it now trains on 1 stock at a time its a csv file I use pandas to load it.
Is there a way to train the model on multiple stocks at the same time? What would be the best approach?
I don't need code just guidance as all my research has failed

**Tags:** time-series, gradient-boosting, boosting


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## 1 answers

### Answer by username_1 on 2022-11-10. Score: 1

The short answer is no.

Time series models model a single time series. If you want to model N time series you need N time series models. XGBoost is no different when used for time series modeling. The only exception to this would be deep learning using transfer learning but that is a different animal.


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