- Jonathan
- Jose
- Mario
- Willian
The following project is a 4th year student project about cryptocurrency prediction using machine learning.
We were planning to make predictions for digital currencies by implementing, evaluating and comparing different machine learning models. We have succeeded. At least we have managed to get good results overall.
- Prophet
- ARIMA
- LSTM
- Simple Exponential Smoothing
Aside to the used models/implementations we have also added two extra functionalities.
- The Statistical Decision-making feature
- The Interactive Dashboard feature
The statistical Decision-making feature is a custom made function created not to tell to the unsuspecting reader who put its hungry eyes on the results presented here - so far - what to do with their money, but to help the minded, cognizant, and even the investor-lover reader to make their own observations and help them to drive their very own future strategic decision-making through the well based and researched demonstrated analysis.
It is based on the predicted close value of the next day, compared to the rules definied on the business case. It returns a 'Sell' or 'Buy' "advice".
The Interactive Dashboard was created in order to display the findings and differences of the models on its results and caracteristics.
It returns the graphs of each model implementation, and the predicted value of a 'x' amount of days.
In order to attempt to achieve a more accurate results the next steps for the statistical decision would be to use a multi-step Time Series Forecasting Model