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1. 1. Adding external factors in Time Series Forecasting : Case study: Ethereum price forecasting

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :José María Vera Barberán; [2020]
   Nyckelord :Time-series; Forecasting; Pattern-based models; ARIMA; LSTM; Tidsserier; Prognoser; Mönsterbaserade modeller; ARIMA; LSTM;

   Sammanfattning : The main thrust of time-series forecasting models in recent years has gone in the direction of pattern-based learning, in which the input variable for the models is a vector of past observations of the variable itself to predict. The most used models based on this traditional pattern-based approach are the autoregressive integrated moving average model (ARIMA) and long short-term memory neural networks (LSTM). LÄS MER