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Hi,
I have an alpha that emits insights.
I want to train my XGBOOST/LSTM model using the factors of the alpha (gap, correlation, volume, etc) and the target should be the result of the trade: profit or loss.
(so I can feed the factors to the model later and get a prediction on the likelihood of a profit )
what is the best practice to do this?
I thought about logging the data and train the model with this data - but it's complicated and the logging is limited.
any advice?
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Alexandre Catarino
Hi Gil Sapir ,
We have recently implemented the ObjectStore that can be used to save data to be used later by the ML model.
I hope this answers your question.
Gil Sapir
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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