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UNWE Article – Crypto Datathon

Prediction of cryptocurrency prices (5 min period) with AR, ARIMA and Neural Network models using R and Python.

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2 thoughts on “UNWE Article – Crypto Datathon

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    It would have been great if you had used what you learned in the first half about log-returns and how they behave in the prediction’s second half. As it stands it seems that you are using the prices to do the prediction, rather than any modification of it.
    There also seem to be several different types of predictions – ARIMA(1, 1, 1) (which some what handles prices vs log-returns) and AR(1) model (which is an ARIMA(1, 0, 0)) – correct me if i am wrong, but you haven’t done any comparisons between the two models? As they are nested, readily available statistical tests could have been used for that part. Also, the final predictions are from which model?

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      The AR(1) seemed to perform the best. Using an ARIMA doesn’t improve things much and it’s not surprising considering what we saw from the autocorrelation plots. The values just aren’t strongly correlated with one another, meaning a higher order model brings very little improvement, if any.

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