hilali-msc / ethereum-price-prediction-using-lstm

Capstone project for the course Deep Learning as part of the master Data Science and Society.

Ethereum Return Prediction using LSTM

Capstone project for the course "Deep Learning" as part of the master "Data Science and Society". Paper title "An LSTM Approach to Predicting Ethereum’s Price Trend Based on Blockchain Characteristics".

I obtained a course grade of 10/10 as a result of this paper. Mind you, this does not imply that the result/code is meaningful in any way, as the grade was solely based on the final paper.

Notes

• Use "hyper-parameter_optimization.ipynb" to see how hyper-parameter optimization was conducted. "testing_models.ipynb" shows the error metrics as well as performance of the trading strategy.
• The final results can be found inside this repository in the document going by the name of "Final Paper.pdf".
• Please don't actually trade on the results found in this paper. There is a (high) chance that applying the models I tested will generate losses in the real-world, as I didn't factor in transaction costs/slippage (and it is probably overfit).
• There is a chance that there are still mistakes present in the code.