Support Vectors Models in time series: an application to cryptocurrencies
Cryptocurrencies, Machine Learning, Support vector machine, recurrent SVR.
In several cases, it is necessary to predict continuous time-dependent variables. As a particular case of this work, we have an interest in predicting the price of cryptocurrencies, which are increasingly popular, where it is seen a high growth and high price variability. In this sense, we aim to forecast the daily closing price of bitcoin, etherium and dash using the support vector machine theory, as well as an adaptation of this methodology to the case of time series forecasting, called recurrent SRV . The results obtained show a substantial gain in the daily forecast, surpassing traditional methods.